The quick service restaurant (QSR) sector is entering 2026 at a pivotal moment. Consumer demand remains resilient, but the operating environment is more complex than at any point in the last decade. Inflationary pressures, labour shortages, evolving customer expectations and rapid technological change are forcing QSR leaders to make sharper, more evidence-based decisions.

While much has been written about emerging QSR trends, many articles stop short of answering the most important question: which trends will genuinely deliver sustainable growth, and which risk becoming costly distractions? 

In 2026, success will depend less on adopting every new innovation and more on prioritising the right initiatives, in the right locations, for the right customers, underpinned by strong data foundations. 

Why QSRs can’t afford to ignore these trends

Globally, the QSR market continues to grow, but that growth is increasingly uneven. According to market analysis of the UK foodservice sector, total market value is forecast to exceed £85bn by 2026, with growth driven largely by QSR and delivery-led formats. 

However, this growth masks significant pressure beneath the surface:

• Labour and food inflation have increased operating costs by 20–30% since 2019, according to hospitality cost analysis and UK inflation data. 
• More than 50% of UK consumers report actively cutting back on discretionary spending, including eating out. 
• Digital interactions now influence the majority of QSR transactions, from mobile ordering and kiosks to loyalty and payment.

Against this backdrop, trends are not abstract ideas — they directly influence network planning, pricing strategy, menu development and customer experience. Brands that understand how these trends play out locally are far better positioned to protect margins and unlock sustainable growth.

Top 7 quick service restaurant trends for 2026 

1. AI as a strategic engine, not just a technology layer 

Artificial intelligence has moved well beyond experimentation in QSR. In 2026, AI is increasingly embedded across forecasting, pricing, labour scheduling and customer engagement. 

Academic and industry research shows that machine-learning-based demand forecasting can reduce forecast error by up to 52%, directly lowering waste and improving operational efficiency. 

Additional industry analysis highlights that AI-enabled forecasting can reduce food waste by up to 25%, improving both sustainability and margins. 

However, the biggest gains come when AI is treated as a strategic capability, not a bolt-on. Without high-quality customer data, location insight and behavioural context, AI risks reinforcing inefficiencies rather than resolving them.

What leading QSRs are doing differently: 

Rather than deploying AI in isolation, leading QSRs are focusing on strengthening the data foundations that sit behind it. This includes improving customer data quality, linking transactional and behavioural signals, and incorporating location-based context into forecasting models. As a result, AI is increasingly used to anticipate demand, optimise decision-making and reduce operational risk, rather than simply automate existing processes.

2. Drive-thru reinvention: speed, accuracy and experience 

Despite the growth of delivery and mobile ordering, the drive-thru remains the backbone of the QSR model. Industry analysis consistently shows that drive-thru accounts for nearly 75% of QSR sales in mature markets.

Key developments shaping 2026 include:

• Voice AI reducing average order time by 20–30 seconds per vehicle 
• Increased use of queue analytics to manage peak-time congestion

Crucially, hospitality research shows that order accuracy and perceived friendliness have a greater impact on repeat visits than speed alone, reinforcing the need for balanced optimisation. 

What leading QSRs are doing differently:

Top-performing QSRs are moving away from uniform drive-thru solutions and instead optimising performance at a local level. By analysing demand patterns by site, time of day and customer mix, they are better able to balance speed, accuracy and service quality. This approach helps direct investment towards the locations and peak periods where improvements deliver the greatest return.

3. Omnichannel ordering and digital transformation (with loyalty at the core)

By 2026, omnichannel is no longer a differentiator — it is an expectation. Customers move seamlessly between apps, kiosks, drive-thru and delivery platforms. 

Industry data highlights that:

• Customers engaging across three or more channels are 2.5x more valuable than single-channel customers. 
• Loyalty members account for over 70% of digital QSR revenue at leading brands.

The challenge lies in orchestration. Fragmented systems and disconnected data undermine both margin and experience. Leading QSRs are investing in a single customer view, unifying transaction, behavioural and location data to understand which channels genuinely drive incremental value.

What leading QSRs are doing differently: 

Rather than treating channels independently, leading QSRs are building a more integrated view of the customer journey. By connecting data across mobile, in-store, drive-thru and delivery platforms, they gain clearer visibility of true customer value and channel interaction. This enables more consistent experiences, better-targeted loyalty strategies and improved understanding of which channels drive incremental growth.

4. Value-driven strategies in a cost-conscious market

Value has re-emerged as one of the defining QSR trends of 2026. According to UK consumer research, more than half of consumers actively compare prices before choosing where to eat. 

Additional findings show that:

• Bundled meals increase average order value by 8–12% 
• Limited-time offers drive trial without permanently eroding price perception

The most effective value strategies are location-specific, using data to tailor pricing and promotions to local demographics, competition and demand patterns. 

What leading QSRs are doing differently

Instead of relying on national price promotions, leading brands are taking a more nuanced approach to value. By analysing local demographics, competitive intensity and purchasing behaviour, they are tailoring offers and bundles to specific markets. This allows them to respond to price sensitivity where it exists, while avoiding unnecessary margin erosion in locations where demand is more resilient.

5. Sustainability and packaging innovation

Sustainability is now a baseline expectation rather than a differentiator. Research indicates that over 75% of consumers expect QSR packaging to be recyclable or compostable. 

Industry data also shows:

• Packaging redesigns can deliver 10–15% material cost savings 
• Food waste contributes 8–10% of global greenhouse gas emissions, increasing pressure on operators to reduce waste 

What leading QSRs are doing differently: 

Leading QSRs are embedding sustainability into operational decision-making rather than treating it as a standalone initiative. By monitoring waste, packaging usage and customer response at a granular level, they are able to test changes, measure outcomes and scale successful approaches. This data-led approach helps balance environmental goals with operational efficiency and cost control.

6. Health, wellness and radical transparency

Health-led eating continues to influence QSR menus. Consumer studies show that over 40% of UK consumers actively seek healthier options when eating out.

Protein-forward and plant-based items continue to outperform category averages, while demand for clear nutritional and allergen information grows. 

What leading QSRs are doing differently: 

Rather than expanding menus uniformly, leading operators are using customer insight to understand how demand for healthier options varies by location and occasion. This allows them to introduce targeted menu changes, refine portion sizes and improve transparency without adding unnecessary complexity. The result is a more relevant offer that reflects local preferences while maintaining operational simplicity.

7. Ghost kitchens and virtual brands: a more disciplined model

Ghost kitchens remain relevant, but success depends on precision. Market analysis shows that location selection and demand modelling are the biggest determinants of virtual brand success. 

Virtual brands are increasingly used to:

• Extend trade area coverage 
• Test new concepts with lower capital risk 
• Optimise delivery economics

What leading QSRs are doing differently:

Successful operators are taking a more analytical approach to virtual brands and ghost kitchens. By combining demand forecasting, delivery radius analysis and competitive mapping, they are identifying opportunities that complement existing estates rather than cannibalise them. This disciplined use of data reduces risk and improves the likelihood of sustainable performance.

How QSR leaders can act on 2026 trends today

Understanding trends is only half the challenge. The real differentiator is execution. 

To translate 2026 trends into commercial advantage, QSR leaders should focus on five practical steps: 

1. Prioritise trends by impact, not hype 

Not every trend will matter equally to every brand. Use data to assess which initiatives will:

• Drive incremental demand 
• Improve operational efficiency 
• Strengthen customer loyalty 

2. Ground innovation in customer insight 

Customer expectations vary significantly by location, demographic and occasion. Advanced segmentation and behavioural analysis help ensure investment aligns with real demand. 

3. Use location intelligence to guide decisions 

From drive-thru optimisation to ghost kitchens, place matters. Understanding trade areas, cannibalisation risk and local competition reduces costly mistakes. 

4. Test, learn and scale 

Pilot new formats, offers and technologies in controlled environments. Measure results rigorously before national rollout. 

5. Build a strong data foundation 

Unified, high-quality data underpins every successful trend — from AI to personalisation to sustainability.

Future outlook: what comes next?

Looking beyond 2026, the QSR sector will continue to converge with retail and digital commerce. Automation will increase, but human service will remain critical. Data will become more central — not just for optimisation, but for resilience. 

The brands that outperform will be those that:

• Invest in insight, not just infrastructure 
• Optimise locally, not just nationally 
• Align innovation with measurable commercial outcomes

In a volatile environment, clarity beats complexity — and data-led decision-making is the most reliable route to sustainable growth. 

Frequently asked questions about QSR trends for 2026

What are the top quick service restaurant trends for 2026? 

The top quick service restaurant trends for 2026 include AI-driven operations, drive-thru optimisation, omnichannel ordering, value-led pricing strategies, sustainability-focused packaging and data-driven personalisation. These trends reflect rising cost pressures, digital adoption and changing consumer expectations across the QSR sector. 

How is AI being used in quick service restaurants? 

AI is used in quick service restaurants to improve demand forecasting, labour scheduling, order accuracy and personalised marketing. By 2026, many QSRs use AI to reduce food waste, optimise staffing and deliver more relevant customer offers in real time. 

Why is value such an important trend for QSRs in 2026? 

Value is a key QSR trend in 2026 because consumers are more price-conscious due to ongoing cost-of-living pressures. Quick service restaurants are responding with targeted value meals, bundles and promotions that balance affordability with profitability. 

Are ghost kitchens still relevant in 2026? 

Yes, ghost kitchens are still relevant in 2026, but they are used more selectively. QSR brands now rely on demand modelling, delivery radius analysis and location intelligence to ensure ghost kitchens are commercially viable. 

What role does data play in QSR trends for 2026? 

Data plays a central role in QSR trends for 2026 by enabling better decision-making across pricing, site selection, customer engagement and operations. Brands that integrate customer, transaction and location data are better positioned to adapt to market changes. 

How can quick service restaurants prepare for the future beyond 2026? 

Quick service restaurants can prepare for the future by investing in strong data foundations, customer insight and flexible operating models. This allows QSRs to test new concepts, optimise locations and respond quickly to evolving consumer behaviour.

Why Share of Wallet matters now 

Customer acquisition costs continue to rise, and the dynamic is even more pronounced in financial services, where competition for deposits, primary current accounts, and long-term savings has intensified. Research from the Harvard Business Review shows that it can cost up to five times more to acquire a new customer than to retain an existing one. Meanwhile, customer expectations have increased, switching barriers have fallen, and digital competitors are often just a click away. Within financial services, Open Banking has further accelerated switching and multi-banking behaviour, giving customers more freedom to distribute their balances across multiple institutions 

Organisations that focus only on acquisition risk spending heavily without ever realising sustainable growth. This is particularly true in financial services, where the cost of onboarding, KYC, AML checks, and compliance activities makes new customer acquisition especially expensive. As noted by Deloitte Insights, financial institutions that prioritise deepening existing customer relationships outperform those that rely heavily on acquisition-led strategies. 

Through Share of Wallet, financial institutions can also: 

• Identify the value of balances customers hold elsewhere, giving institutions insight into hidden opportunities for deposit and investment growth. 
• Understand which demographics, products and regions are outperforming the base, simplifying the identification of priority growth segments. 
• Access aggregated SOW metrics and periodic reporting, enabling customer-level and portfolio-level performance tracking. 
• Track KPIs linked to long-term strategic initiatives, connecting balance growth with broader business outcomes. 
• Use granular data to inform personalised communications, targeting customers based on wealth indicators, behaviours and potential. 

This guide explains what share of wallet means in a financial-services context, how to calculate it using balances and asset concentration, why it matters strategically, and the practical, analytics-driven methods institutions use to increase it. Drawing on use cases across banking, savings, credit, and wealth management — including work CACI delivers — this guide shows why leading FS organisations now treat balance-based SOW as a cornerstone of sustainable growth. 

What is Share of Wallet? 

Share of Wallet (SOW) in financial services refers to the proportion of a customer’s total account balances or savings “wallet” that they hold with your institution across products such as current accounts, savings, ISAs, investments, mortgages or personal loans. 

For example, if a customer has total liquid savings of £40,000 and holds £10,000 of those balances with your bank, your SOW is 25%. 

This measurement applies across the sector: the percentage of a customer’s investable assets held with a wealth manager, the proportion of deposits concentrated with a building society, or the share of credit balances placed with one provider. 

SOW provides a more complete understanding of customer value by: 

• Revealing the total wealth picture, rather than only internal balances. 
• Highlighting how much money customers hold elsewhere, enabling accurate opportunity sizing. 
• Filling gaps in financial understanding that internal data alone cannot provide. 

Share of Wallet vs Market Share

The two metrics assess very different dynamics:

• • Market share measures your institution’s total balances or products across the market. 
  • Share of wallet measures the proportion of each individual customer’s financial life that you hold. 

A bank may have high market share yet a low share of wallet per customer — signalling weak relationship depth. Conversely, a smaller provider might have very high wallet share among a loyal customer base. 

SOW also supports strategic decision-making by enabling: 

• Tracking of balance growth KPIs across segments and product lines. 
• Monitoring long-term performance such as deposit acquisition, wealth onboarding and cross-product engagement. 
• Identifying “headroom” — the additional balances customers are likely to hold elsewhere that could be captured. 

How to calculate share of wallet 

The Basic Formula 

SOW (%) = (Balances held with your institution ÷ Customer’s total balances) × 100

Example: 
• Total savings: £60,000 
• Balances with your bank: £15,000 
• SOW = 25% 

Data Sources for Calculation

• Internal account and balance data 
• Open Banking and aggregation tools 
• Customer research panels 
• Predictive modelling and machine-learning estimation of held-away balances 

A strong SOW calculation enables institutions to: 

• Combine customer-level balance estimates with postcode-level and product-level data for a 360° view of financial behaviour. 
• Use CACI Retail Finance Benchmarking to understand typical wallet sizes, competitor penetration and localised patterns. 
• Integrate wealth estimates into modelling, segmentation and pricing cohorts. 

Common Challenges

• Hidden balances not visible to individual providers 
• Volatile liquidity movements 
• Categorisation differences across product types 
• Life-stage and macroeconomic factors influencing wallet size

Why Share of Wallet Matters

Cost-Efficient Growth 

Deepening customer relationships by capturing more of their financial life is significantly more cost-effective than acquiring new customers. Increasing balance concentration boosts revenue per customer while lowering cost-to-serve. 

Customer Retention and Loyalty 

Customers who place a higher proportion of their savings or investment assets with one institution demonstrate far stronger loyalty and lower churn. 

Lifetime Value 

As wallet share increases, so does Customer Lifetime Value (CLV). Customers with deeper financial relationships are more likely to take mortgages, lending products, savings accounts and wealth services. 

Strategies to increase Share of Wallet

Segment Customers by Potential 

Not all customers have the same growth potential. SOW helps identify:

• High potential, low share customers with substantial held-away balances 
• High value customers to defend and deepen 
• Lower potential segments requiring reduced investment 

CACI helps institutions uncover these opportunities using demographic, geographic and behavioural insight. 

Cross-Selling and Upselling 

Examples include: 

• Encouraging current-account-only customers to open savings products 
• Moving savers from low-yield accounts to higher-value fixed-term or investment products 
• Introducing ISA or wealth solutions to customers showing investment readiness 

Next best product models identify optimal timing. 

Loyalty, Rewards and Relationship Pricing 

Mechanisms include: 

• Preferential rates for customers consolidating savings 
• Bundles linking savings, current accounts and credit 
• Incentives for salary mandates or account funding 

Bundling and Value Propositions 

Product bundles and integrated financial management tools increase stickiness by offering convenience, clarity and control. 

Customer Experience 

Ease, trust and service quality materially influence wallet share. Positive digital and branch experiences translate directly into balance consolidation. 

Financial Services use case: Share of Wallet in banking 

Customer-Level Coding 

Banks assess the percentage of customer balances they hold to identify:

• Customers with significant held-away funds 
• Investment assets managed by competitors 
• Opportunities to deepen primary relationships 

Savings Behaviour and Headroom 

Balance-based analysis distinguishes between:

• Fixed savings 
• Variable savings 
• Investment holdings 

Customers with large variable balances but low SOW offer clear growth potential. 

Segmentation by Demographics 

Older customers often consolidate more; younger customers diversify more widely. 
CACI’s Fresco segmentation adds further behavioural and life-stage context. 

Monitoring and Tracking 

Modern analytics track: 

• Balance concentration shifts 
• Flow of funds in and out of held-away accounts 
• Changes in product mix and adoption patterns 

How Institutions Use SOW

• Identify and quantify customer-level opportunities 
• Use CACI Retail Finance Benchmarking and location intelligence to find geographic hotspots 
• Target segments with low share but high growth capacity 
• Avoid unnecessary rate rises for customers already showing high SOW Provide frontline teams with estimated SOW indicators for personalised engagement 

Sector perspectives beyond Financial Services

 Retail and E-commerce  

Supermarkets compete to become the primary shopper destination. Loyalty cards, personalised coupons, and basket-building promotions all increase wallet share. E-commerce platforms use recommendation engines and premium memberships to keep customers buying within their ecosystem.  

Telecoms and Media 

Quad-play packages dramatically increase wallet share by consolidating multiple services into one bill. Customers who bundle are less likely to switch because of the perceived inconvenience of managing multiple providers.  

B2B and Professional Services  

For B2B firms, wallet share often means expanding into adjacent service areas. A consultancy may start with strategy and then cross-sell into analytics, technology, or managed services. Increasing wallet share in B2B builds long-term, multi-service relationships that are resistant to competitor approaches. 

Share of Wallet pitfalls and limitations 

Financial services face additional challenges: 

• Over-marketing: too many rate-driven offers can reduce trust. 
• Cannibalisation: shifting balances between products may not increase total value. 
• Balance volatility: savings can move rapidly in response to macro-economic signals. 
• Privacy and regulation: strict rules govern the use of customer financial data. 

Institutions should balance ambition with transparency and ethical standards. 

Advanced Share of Wallet analytics: The CACI approach 

Real differentiation comes from analytics: 

• Predictive modelling: estimating total wallet and held-away balances. 
• Uplift modelling: identifying which customers are likely to consolidate more funds. 
• Controlled experimentation: validating rate changes or marketing interventions. 
• Dashboards: tracking SOW in real time across segments and product lines. 

CACI’s data science services help banks turn SOW from a descriptive measure into a predictive, prescriptive engine for long-term balance growth. 

Share of Wallet implementation roadmap 

• Assess: measure baseline balance concentration. 
• Prioritise: identify customers with high potential and low current share. 
• Design: develop targeted financial strategies — pricing, product prompts, digital journeys. 
• Execute: deploy at the right moment with meaningful personalisation. 
• Measure: track responses, adjust propositions, and optimise. 

Evolving Dynamics of Wallet Share 

Wallet share in FS is evolving through: 

• AI-powered personal finance tools influencing balance allocation. 
• Open Banking transparency enabling better competitor comparison. 
• Cross-category mapping (e.g., savings vs investments). 
• ESG-driven decision-making shaping where customers place their assets. 

Conclusion 

Share of Wallet is more than a KPI — it is a growth framework grounded in balance concentration and trusted financial relationships. By accurately measuring and acting on SOW, institutions can increase profitability, reduce churn, and deepen their role in customers’ financial lives. 

CACI’s expertise in data science, segmentation, and customer insight helps banks move from generic cross-sell to intelligent, targeted strategies that materially increase the proportion of savings, balances, and financial value customers hold with them. 

Share of Wallet FAQs 

1. What is share of wallet in banking? 

Share of wallet in banking refers to the proportion of a customer’s total account balances or savings that they hold with a specific financial institution. 

2. How do banks calculate share of wallet? 

Banks calculate share of wallet by dividing the balances a customer holds with them by the customer’s estimated total savings or assets, including held-away funds. 

3. Why is share of wallet important for financial institutions? 

A higher share of wallet increases customer lifetime value, improves retention, and strengthens the institution’s role as the customer’s primary financial relationship. 

4. What is a good share of wallet percentage for banks? 

A strong share of wallet typically means holding the customer’s primary current account and a significant portion (often 50% or more) of their liquid savings. 

5. How can banks increase share of wallet? 

Banks increase share of wallet by offering competitive savings rates, personalised product recommendations, relationship-based incentives, and frictionless digital experiences that encourage customers to consolidate balances. 

6. What are held-away balances in financial services? 

Held-away balances are savings or investment funds that a customer holds with other institutions, which represent potential share of wallet growth opportunities. 

7. What affects a customer’s share of wallet? 

Factors include trust, interest rates, digital experience, financial goals, risk appetite, and the convenience of managing multiple financial products in one place. 

8. How does share of wallet relate to customer loyalty? 

Customers who allocate more of their balances to one institution typically show higher loyalty, lower churn, and longer relationship tenure. 

9. What tools do banks use to measure share of wallet? 

Banks use predictive modelling, Open Banking data, demographic profiling, and internal balance analytics to estimate total wallet size and identify held-away funds. 

10. What is a share of wallet strategy in financial services? 

A share of wallet strategy focuses on increasing the proportion of a customer’s total balances, deposits, or investable assets held with the institution through targeted engagement and personalised offers. 

Why Share of Wallet analysis matters

Most financial institutions recognise that retaining customers is more cost-effective than acquiring new ones. Yet few have a reliable method for understanding how much of a customer’s total savings, deposits or investment balances they actually hold, or how much value sits hidden in other institutions. This is where Share of Wallet Analysis becomes indispensable. 

In financial services, Share of Wallet (SOW) reflects the proportion of a customer’s total financial holdings—savings, current account balances, fixed-term deposits, investments or unsecured lending—held with your institution. Share of wallet analysis refers to the methods, data and models used to measure, estimate and interpret a customer’s total balance wallet, including held-away funds. Done well, it uncovers hidden balance headroom, identifies consolidation opportunities, highlights attrition risk, and provides a roadmap for profitable balance growth. 

In this article, we explore what share of wallet analysis means within financial services, how it is conducted, common analytical methods, and how advanced modelling transforms SOW from a static metric into a powerful engine for deposit growth, cross-sell, retention and customer value expansion. 

👉 If you’re new to the concept of wallet share itself, start with our Definitive Guide to Share of Wallet for Financial Services and then return here for the measurement and analysis deep dive. 

What is Share of Wallet analysis? 

Share of Wallet Analysis in financial services is the process of calculating and interpreting the proportion of a customer’s total account balances held with your institution versus competitors. It goes beyond the raw SOW percentage to understand why customers distribute balances the way they do, what balance growth potential exists, where consolidation opportunities lie, and which customers present the strongest long-term value. 

In practice, SOW analysis involves: 

• Measuring balances held with your institution 
• Estimating total customer wallet size, including held-away savings and investments 
• Identifying patterns across customer, product and demographic segments 
• Using predictive analytics to model future balance consolidation and risk 

Methods of Share of Wallet analysis 

1. Survey-Based Approaches 

Historically, banks and building societies often relied on surveys asking customers where else they held savings or investments. 

Strengths: 

• Useful for capturing attitudinal data (trust, preference, propensity to consolidate) 
• Can identify perceived gaps in relationships 

Weaknesses: 

• Self-reported balances are often inaccurate 
• Customers underreport or forget held-away accounts 
• Hard to scale reliably 

📖 Research published in the Journal of Marketing Research shows that self-reported financial behaviour often underestimates total balances. 

2. Internal Transactional and Balance Data 

Banks, building societies and wealth managers hold accurate information about the customer’s primary account balances—current accounts, savings, term deposits, ISAs, loans and investments. 

Strengths: 

• Highly accurate, real-time data 
• Enables granular behaviour analysis (flows in/out, volatility, deposit stability) 
• Supports segmentation and life-stage profiling 

Weaknesses: 

• Limited to balances held with your organisation 
• Does not show the size of competitors’ holdings 

This is the foundation for customer-level SOW coding but requires external data or modelling to understand the full wallet.

3. Third-Party Panels and Benchmark Data 

Industry benchmarks—such as regulatory publications, anonymised credit bureau data or aggregate financial panels—help institutions estimate likely total wallet sizes across segments. 

Strengths: 

• Offers a market-level perspective 
• Useful for comparing your penetration against competitors 

Weaknesses:

• Panels may not align perfectly with your customer mix 
• Insights are directional, not customer-specific

A Deloitte report on financial services highlights that panel data supports competitive context but must be calibrated to segment differences. 

4. Predictive Modelling 

This is the most advanced and reliable approach for FS. Predictive models estimate total customer wallet size, including balances you cannot see, using behavioural indicators, demographics, product mix, income signals and external datasets. 

Techniques include: 

• Regression models linking known balances to inferred total wealth 
• Machine learning models using hundreds of variables to predict wallet size 
• Uplift modelling to assess which actions drive incremental consolidation 
• Propensity-to-save and propensity-to-move models 

At CACI, we combine internal balance data, segmentation, geography and market-level insight to produce a highly accurate picture of held-away balances, wallet potential and consolidation opportunity. 

The process of Share of Wallet analysis

Step 1: Define the Financial Category 

Define what counts as the “wallet”: 

• Liquid savings 
• Fixed-term deposits 
• Current account balances 
• Investment assets 
• Unsecured lending exposure 
• The category definition shapes both measurement and modelling. 

Step 2: Collect and Integrate Data 

Bring together: 

• Internal balance data 
• Product holdings 
• Customer demographics 
• External panels and benchmarks 
• Predictive model outputs 

This is where CACI’s expertise in customer data integration and Retail Finance Benchmarking becomes essential.

Step 3: Calculate Current Wallet Share 

Apply the adapted FS formula: 

SOW (%) = (Balances held with you ÷ Estimated total customer wallet) × 100 

Step 4: Segment and Prioritise

Segment customers into actionable groups: 

•  High wallet, low share (big consolidation opportunity) 
• High wallet, high share (protect and retain) 
• Low wallet, high share (profitable but low headroom) 
• Low wallet, low share (limited upside)

Step 5: Apply Predictive Analytics 

Model: 

• Total wallet value 
• Likely held-away balances 
• Customer headroom 
• Propensity to consolidate 
• Product-specific opportunities (savings, ISAs, term deposits, investments) 

Step 6: Translate Insight into Action 

Actions include: 

• Targeted savings growth campaigns 
• Relationship pricing for consolidation 
• Fixed-term renewal strategies 
• Investment readiness triggers 
• Personalised engagement sequences 

Why advanced analytics makes the difference 

Basic wallet share tells you the percentage you currently hold. Advanced analytics tell you how much you could hold, how to win it, and where the risks are. 

Predictive Power 

Models forecast wallet potential for each customer, identifying those most likely to consolidate balances. 

Uplift Measurement 

Uplift modelling isolates the true incremental effect of actions—ensuring incentives are only offered where they change behaviour. 

Dashboards and Visualisation 

Dynamic dashboards allow product, marketing and risk teams to track: 

•  Wallet share 
• Flows in and out 
• Consolidation patterns 
• Segment-level performance 

Forrester research highlights that organisations adopting advanced analytics see significant improvements in customer experience outcomes. 

Sector examples of Share of Wallet analysis

Banking and Financial Services 

Banks use SOW analysis to identify: 

• Customers with large savings held externally 
• Deposit consolidation opportunities 
• ISA or investment readiness 
• Mortgage customers without savings or wealth relationships 

For example, a customer with high income and low internal savings may hold significant deposits elsewhere—representing high wallet headroom.

Retail and E-commerce (Contextual Comparison Only) 

Retailers use similar principles, but FS analysis focuses on balances, not spend. 

Telecoms and Media (Conceptual Parallel) 

Bundling logic informs FS strategies such as linking current accounts, savings and credit. 

B2B Services

Professional services firms use wallet analysis to expand into adjacent advisory domains. 

Pitfalls in Share of Wallet analysis

• Over-reliance on surveys
• Poor data governance or misuse of Open Banking data
• Treating all customers as having equal wallet potential
• Short-term incentives that erode long-term margin
• Misinterpreting volatility in savings (seasonality, life events)

Future of Share of Wallet analysis 

The next decade will further accelerate SOW capability through: 

• AI-driven next-best-action models 
• Real-time balance monitoring through connected data ecosystems 
• Cross-category household finance modelling 
• ESG-aligned financial behaviour analysis 

Organisations using AI-led wallet prediction will outperform those relying on historical balances alone. 

Conclusion

Share of Wallet Analysis turns a simple metric into a strategic growth engine. In financial services, it reveals how much of a customer’s total savings, deposits and investments you truly hold, where your hidden opportunities lie, and what actions will maximise customer lifetime value. 

By combining advanced analytics, data integration, segmentation and customer insight, financial institutions can unlock held-away balances, increase consolidation and strengthen their role in customers’ financial lives. 

At CACI, we help institutions turn SOW analysis into measurable growth—building models, integrating data and designing targeted interventions that drive long-term, profitable balance expansion. 

This year’s MCA Food to Go conference unveiled the key growth drivers, future trends and exciting developments shaping the sector. It highlighted everything from innovative technology and formats to trendsetting menus and marketing, ultimately exploring how successful brands are navigating market challenges.

At the conference, I showcased transaction trends and growth opportunities emerging in 2026 based on three months of data from CACI’s Brand Dimensions dataset. By tracking 30+ food to go brands from November 2025 to January 2026, I assessed the trends and opportunities fuelling growth questions this year. 

Here is what the data revealed. 

Food to Go transaction trends & growth opportunities in 2026

The findings showed: 

• +6% YoY revenue growth in the Cafés & Coffee Shop market 
• A slight decrease in Quick Service Restaurant (QSR) transactions, but a slight increase in Average Transaction Value (ATV)  
• Transactions and revenue dropping across the wider F&B sector

Which brands are leading industry trends in 2026?

From the 30+ up-and-coming and major players in the food to go sector tracked, I identified the leading brands as those achieving YoY growth above inflation and sorted them by increase in growth percentage. 

Premium healthy lunches: Atis & Farmer J

Consumers continue to prioritise premium healthy lunches this year.  

The leading brands were Atis, growing 140%, and Farmer J, growing ~30%. Atis’ skyrocketing growth is driven by the opening of a third new space in the last year. While substantial and impressive, it is the smallest brand in CACI’s Food to Go tracker, meaning the overall GBP shift in the market is small.  

The largest share of the customer mix for these brands comes from CACI’s Acorn profiles Prosperous Professionals at 15% of spend followed by Up-and-coming Urbanites at 11%. 

For new entrants, the challenge to growth is proving value in each transaction, precise targeting and mission expansion without undermining the brand or cannibalising sales. 

Continued growth in chicken QSR: Popeyes, Wingstop & Slims

Consumers continue to seek indulgence and novelty. In the chicken QSR sector, our findings concluded Popeyes grew ~30%, Wingstop ~20% and Slims ~9% (who were +46% in the first quarter of the year). While this may counter the premium healthy lunch trend, consumers are finding ways to balance health-conscious choices with indulgent ones. 

Caffeine & matcha on the rise: Blank Street & Grind

Both Blank Street and Grind grew over 20%, indicative of the brands’ innovative products, strong social media presence and matcha-led menus. These brands have evidently appealed to younger, experience-driven consumers by creating excitement through their product innovation. 

Established brands are driving growth by harnessing loyalty 

The biggest takeaway is that while new entrants win on excitement, established brands win on loyalty.  

New brands have brought excitement, and with that, percentage growth, but most saw YoY growth rates slow across the year. Meanwhile, more established brands like Pret a Manger, Costa, Starbucks and McDonald’s saw stronger growth in the latest quarter. When assessing actual pounds versus percentage growth, established brands are back growing and seeing very substantial sales gains. This reiterates the impact of loyalty on long-term growth.  

The formula of the current state of the market then becomes:  

Excitement = short-term percentage growth. Loyalty = long-term monetary growth. 
 
New brands, social media influence and new cuisine are fuelling excitement. Loyalty is driven by familiarity, perceived value, brand resonance and communication. Brands that can achieve a sweet spot between both are poised for sustainable growth. However, our findings suggest tension between excitement and loyalty. This prompts brands to reflect on how to maintain excitement or build customer loyalty.  

Four strategies to drive growth in a tough climate

1) Having the right products in place 

Brands must understand how to appeal to existing customers and excite new ones. Product and menu innovation should be strategically considered to open new missions and tailor to the right locations, dayparts and missions.

2) Getting the right space

While growth can be achieved by acquiring new spaces, established brands are always optimising their spaces to reach the right people, in the right place, at the right time. This is why some brands are shifting to drive-through locations as town centres decline and why many have opted to offer FMCG products in the chilled sections of supermarkets.

3) Appealing to customers through the right message 

Tailored content sent to the right target group at the right time with the right incentive is critical to success. 

4) Delivering with the right service

Profitably staffing each location, determining which locations will best suit trialling self-service kiosks and avoiding alienating or upsetting customers who value your brand’s personal service are critical considerations.

This is often easier in the new entry “excitement” phase, but new and established entrants must constantly evaluate that they have the right mix of these factors to remain relevant in a rapidly changing market. Each of these strategies has a ‘people, place and time’ lever that can be pulled to maximise growth by leveraging customer loyalty.  

How CACI’s Brand Dimensions can help your Food to Go business thrive

With so much complexity in the food to go sector, brands need more than just internal customer data to keep on top of the mix. Supplementary market data through CACI’s Brand Dimensions can help you answer your growth questions, combining the right data with the right tools to project long-term growth through the right mix of products, services, places and messaging. 

Highly detailed, timestamped transaction data is at the heart of Brand Dimensions, indicating anonymised customers and specific outlets to infill any data gaps and gain unique performance and competitor outlet insights.

When combined with anonymised mobile activity data and demographic classifications, it creates a cohesive base to address the people, place and time levers driving growth. This can also be topped off with lifestyle attributes linked to those demographics, competitor location data and competitor sentiment data. 

Through this, businesses can better prepare for the future by understanding consumer behaviour at brand level. 

Although Brand Dimensions is typically tracked on a monthly basis, these findings have been summarised quarterly for this blog.  

If your brand could benefit from these data insights, book a Brand Dimensions demo with us. 

What is subscription fatigue?

Subscription fatigue refers to consumers’ deteriorating interest in a subscription or service, resulting in their cancellation. This is often due to feeling overwhelmed by their numerous subscriptions or losing sight of the value each subscription brings. It goes hand-in-hand with churn, where uncertainty, mental exhaustion and subscription overload leads to diminished satisfaction with the subscription experience.  

What is causing subscription fatigue? 

With the ever-increasing number of subscriptions consumers have, decision overload is inevitable. Mounting costs, managing multiple accounts and the pressure to maximise each subscription all contribute to declining satisfaction. When value is unclear, questioning a subscription’s worth surfaces. 
 
Value must therefore be constantly reiterated and subscriptions models must be flexible enough to meet consumers’ unique needs. Signs of fatigue must be identified early on and actions to mitigate fatigue must be taken.  
 
CACI understands the challenge: people want convenience and personalisation, but they also want affordability and control. 

Over-subscription

Subscribing to and managing multiple subscriptions can be mentally draining. The simple fix in consumers’ minds is typically to unsubscribe, even if the service itself is not the problem.

Inability to reinforce value

If consumers feel that they are paying for a service they do not use, the feeling will quickly lead to subscription fatigue. When it comes to subscriptions, low perceived value or service underutilisation are often the driving factors behind cancellations. If value cannot be demonstrated, even your most loyal subscribers may be lost.

Lack of flexibility

When feelings of frustration or overwhelm creep up among the plethora of subscriptions a consumer has, offerings that do not feature flexibility are likely the first to go. Rigid plans will not appeal to already-fatigued consumers. If subscribers feel as though they maintain control over their subscription, they will be easier to retain and keep satisfied. Establishing tiered memberships, flexible pricing, pause options, add-ons or various payment plans can help rectify this.  

How can brands fight subscription fatigue? 

Subscription fatigue may be inevitable within an oversaturated subscription landscape, but understanding the origin of fatigue and the strategies that your organisation can implement to combat this will make a tremendous difference. Leveraging predictive modelling, customer insights and data and segmentation are among the most effective approaches.

Use predictive modelling

AI-driven predictive models forecast customer behaviours and guide the next best actions. Proactive retention and upsell strategies can therefore be developed, resources can be prioritised towards customers with the highest potential and a measurable performance uplift can be seen in metrics like LTV, conversion and engagement. 

Focus on customer insights 

By integrating transactional, behavioural, attitudinal and external data, CACI helps you attain a comprehensive view of your subscribers that will improve your decision-making across acquisition, retention and product development. 

These insights help you:

• Build strategic confidence by grounding it in real customer behaviour  
• Identify high value customers 
• Understand churn drivers 
• Uncover growth opportunities 
• Benchmark performance against your competitors 
• Better understand your position within the market  
• Spot underperforming segments or categories where competitors are gaining share

Grounding strategic decisions in external evidence also improves internal storytelling and stakeholder alignment. 

Focus on acquisition through segmentation

Poor segmentation drains budget by targeting low-value audiences. Without precise targeting, campaigns miss the mark and media mix decisions lack data-driven optimisation.  

CACI’s bespoke segmentation capabilities give you intuitive, data-rich segments reflective of the diversity of your customer behaviours, values and attitudes. This enables personalised marketing and CRM journeys, enhances media targeting and campaign ROI and bolsters strategic planning by revealing which segments to grow, retain or re-engage across three core areas: 

• Data: Curated, high-quality foundational data with diverse input lenses and no personally identifiable information (PII).  
• Segment simulation and validation: Segment-level data layer, validation to assess predictive accuracy with guardrails in place and performance audited.  
• Persona enhancement: Defined by segment characteristics and enriched with psychological and behavioural traits, every step is tested by experts to ensure it is structured, auditable and iterative.

Through this tailored approach, CACI equips you with segmentation that reflects your customers, leading to better decision-making, campaigns and long-term growth.

How CACI can help you overcome subscription fatigue

CACI helps subscription brands unlock growth by transforming fragmented customer data into actionable insight. Through advanced data science and AI-powered decisioning, we support acquisition, retention and personalisation at scale. 
 
We can help you:

• Build deeper customer understanding and target the right audiences 
• Forecast behaviour, improve retention and justify investment 
• Turn insights into action across media and CRM 
• Simplify data and bridge capability gaps

To find out more about how your organisation can successfully overcome subscription fatigue, get in touch with us.

A competitive, complex consumer landscape

Competition has never been more intense in the dynamic and growing consumer health and wellbeing sector. 2025 has seen new market entrants like hair loss treatment company Hair + Me, any number of weight loss services like Juniper and SheMed high on social media feeds and supermarket Morrisons in partnership with Phlo moving into the on-demand online healthcare space alongside existing high street giants Boots, Superdrug and Asda.

This new and intense competition also comes with a new reality: increasingly fragmented consumer behaviour that upends traditional marketing assumptions.

Younger age cohorts drive healthcare growth

Our Voice of the Nation (VOTN) survey examining consumer sentiment finds Gen Z and Millennials in the driving seat of the elective healthcare market. Weight-loss treatments like Mounjaro and Ozempic are expected to surge by 40% in 2025 due to these younger age cohorts.

Notably, Gen Z shows equal interest across genders, unlike older age groups where women dominate. Cosmetic treatments are also gaining traction, with well over 10% of Gen Z and female Millennials planning to pay for them, compared to less than 3% among Gen X and Baby Boomers.

While aesthetics is clearly playing a role, other deeper consumer motivations are also emerging.  Notably, survey respondents who consider health a top national issue are significantly more likely to self-fund treatments. Among Gen Z males in this group, 16.2% plan to pay for weight-loss treatments in 2025 — well above the average of 4.9%. And just as importantly, the VOTN data somewhat counterintuitively shows that demand for elective healthcare products and services in general spans both affluent and less affluent groups.

Age-related wellness and health products drive innovation

In short, our VOTN data reveals a complex blend of beauty, wellness, and proactive health management, with younger generations investing in elective healthcare to enhance both how they feel and how they look.

This trend is reflected in the innovation and increasingly digital activation seen in the fertility and female health space relevant to these age cohorts. Period care pioneer Daye is launching a new at-home hormone testing service for a host of biomarkers like reproductive hormones, thyroid function and Vitamin D. Male fertility company, testhim, which provides consultations, testicular scans, sperm DNA and other diagnostic testing, is also launching specialist fertility supplement testhim M+and a groundbreaking online monthly support group.

Complex, demanding consumers require sophisticated, multi-layered segmentation

So, with Gen Z and Millennials increasingly self-funding weight loss, cosmetic treatments and holistic wellness products and services of all kinds, DTC and e-commerce healthcare brands must truly rethink how they engage with this increasingly data-savvy, image-conscious audience. Informing integrated campaigns that blend social commerce, influencer marketing, paid advertising, organic and direct marketing content. Our VOTN survey also found that nearly two-thirds of Gen Z consumers (63%) have purchased goods and services via a social media platform like TikTok Shop and Instagram, making this a crucial channel for healthcare businesses to understand and potentially utilise.

But to do that effectively in practice, DTC and e-commerce healthcare brands need more than just surface-level insights. They need robust, layered data foundations that help them target the right consumer with the right kind of message at the right time in the right place. Even with first-party consumer data, it’s a significant challenge. Without it, reaching existing or identifying potential customers is almost impossible for brands.

You can see an example of this in our VOTN survey, which showed that for weight loss treatments, there appears to be greater levels of demand both at the more affluent end of our Acorn segmentation spectrum *and* at the least affluent end, potentially for differing reasons.

This requires integrating geodemographic, behavioural, lifestyle, and attitudinal data to move beyond ‘off-the-shelf’ consumer segments and into understanding consumers in a deep way that understands the likelihood of them engaging with specific healthcare products and services and why – enabling brands to drive efficient spend on the right customers – and remove disinterested or low-value ones – in a market with such broad appeal

It’s also only by taking this multi-layered data approach healthcare brands can build strategic data-driven campaigns that resonate on a genuinely personal level in the manner desired by younger generations. Critically, delivering on the perennial, somewhat paradoxical Gen Z demands for high levels of privacy, but also similarly high levels of personalised products and brand messaging.

Turn insights into activation for D2C and e-commerce health campaign success

But as we know, data, in isolation, holds limited value. Its real power is unleashed through activation – the transformation of insight into strategy. And in a world where consumer expectations are rising and attention spans are shrinking, the ability to deliver timely, relevant, and meaningful engagement is an outright competitive advantage. And it can only be achieved through a deep, data-driven understanding of people.

For D2C and e-commerce health brands, this understanding and successful activation requires them to:

• Identify high-value customer segments for targeted acquisition and retention
• Predict churn and retention patterns within subscription-based models
• Inform campaign messaging with real-world consumer behaviours and motivations
• Develop nuanced personas reflecting not just demographics, but attitudes, values, and lifestyle choices
• Personalise content across relevant digital channels, from email to in-app experiences
• Build lookalike audiences for acquisition campaigns on platforms like Meta and Google
• Optimise digital spend by measuring performance and refining segmentation over time

This is where the transformation power of comprehensive datasets, such as CACI’s Ocean database, which offers over 700 variables at an individual and household level, comes in. Ocean includes everything from financial situation, media consumption and digital behaviours to lifestyle preferences like veganism and exercise to whether consumers have a smart watch or fitness band.

When combined with geodemographic tools like Acorn – segmenting over 1.6 million UK postcodes using more than 800 variables – and supported by bespoke data analysis, brands can unlock a truly multidimensional view of their audiences wherever they are.

This approach allows brands to move beyond generic targeting and into a space where campaigns are not only more relevant but also more respectful of consumer expectations – a win-win for younger cohorts who dislike intrusive and irrelevant brand messaging but demand personalisation nonetheless!

Data insight for a dynamic healthcare future

As healthcare consumers’ expectations evolve and the consumer health and wellbeing market with it, so must the strategies brands use to engage them. Success for D2C and e-commerce healthcare brands doesn’t just hinge on understanding who consumers are today — it’s about being able to anticipate who they’re becoming even as new healthcare technologies, products and devices become available. By being able to able to identify and engage high-lifetime value customers as early as possible, brands also have a greater chance to capture markets as they evolve.

The effectiveness of multi-layered segmentation in improving marketing precision now – and as AI becomes more integrated – is well established. CACI’s ability to deliver on this today with our consumer data and bespoke strategic segmentation capabilities ensures brands are future-ready

Data isn’t just a tool – it’s a strategic asset. Brands that invest in sophisticated segmentation and activation today will be best placed to drive sustainable growth tomorrow.

Speak to our healthcare consumer segmentation specialists today.

As attitudinal segmentations are usually based on surveying a smaller sub-group and not based on data which can be easily applied to customers on your database, bridging attitudinal segmentations can be a challenge and is not always a straightforward process. However, it is a great way to provide a consistent customer experience.

So, what is attitudinal segmentation and what considerations should an organisation have when it comes to their approach for bridging an attitudinal segmentation?

What is attitudinal segmentation & how to bridge an attitudinal segmentation

Attitudinal segmentations are typically created using data from quantitative surveys. They can be a powerful tool for delivering rich insights into customer and prospect mindsets and provide a valuable framework for organisations to engage customers effectively through an in-depth understanding of their needs, attitudes and motivations.

Being able to treat customers consistently throughout the marketing funnel helps to establish a relationship with them and deliver resonating messages that will drive increased engagement. Once someone becomes a customer, they will expect to see the same messages that originally struck a chord with them reflected and developed in their ongoing journey with you.

The economic and social disruption since the pandemic has permanently changed consumers and their expectations of brands, so ensuring your online messaging aligns with these changes is increasingly important. We consistently see organisations that are personalising messaging for their customers increasing their market share, net promoter scores, return on investment and profitability. With this in mind, being able to make your attitudinal segmentation actionable on your database should be a key part of your customer engagement strategy.

Key questions to address the challenges of bridging an attitudinal segmentation onto your customer base

There are no two ways about it – data is key to tackling this challenge and making it actionable. To achieve this, you should ask the following five questions to get started:

• Where and who created the segments? Were the segments created by your organisation or a media/research partner? This is pertinent to understanding if you can get to the raw data or in understanding the level of granularity of data you can obtain.
• What data is there? Do you have access to the responder level data or tables by segment or Pen Portraits? The data you can reach will determine the method of bridging that can be used.
• Were questions only posed to your customer base or to the wider population? What types of questions were asked and were they personal to the organisation or more generalised? This can impact the resulting solution.
• Are there any behavioural traits reported within the data that were part of the same survey? Wider data beyond pure attitudes can be helpful to model this back to the database.
• Were any demographic questions asked or was postcode captured? This can help the process of creating the link between segments and customer base.

While bridging an attitudinal segmentation can be challenging, these questions will help identify how simple or complex the solution will be.

Key techniques for bridging attitudinal segmentation

Depending on the granularity of the data your organisation has access to, the following techniques can be leveraged:

• Responder level data: As this is the most granular form of data, it produces the most accurate results. Techniques here include modelling each of the segments by using a mix of the responder data and CACI’s own data to score this up against a customer database before validating this against the responder panel.
• Tables by segment: We can compare each customer’s results to the segment averages based on a combination of multiple data points. Validation is key through profiling and sense checking the segment distribution.
• Pen Portraits: Here we would use a rules-based approach to recreate segments based on high-level views of the segment to capture the different blend of information that you have to bridge the data. As before, the final step of validation is key to ensuring the solution’s accuracy.

If raw data is inaccessible or unavailable, the following alternative methods can support:

• Adding golden questions to market panels: This will provide more demographic and behaviour traits which support the bridging process.
• Surveying the whole customer base with golden questions: Responses can often be skewed to particular segments, however, and some consumers may be more inclined to answer than others.

Considerations at the start of an attitudinal segmentation journey

Including key customer traits

When beginning an attitudinal segmentation, our first recommended consideration would be to include some key customer traits. Including additional questions such as demographic markers (postcode, gender and age band) will support segmentation mapping on to the database.

Cross-team engagement

Cross-team engagement will be invaluable to ensure the segmentation meets goals and drives value. This will help flesh out what the segmentation will be used for now and in the future, as well as gauging what you need from the segmentation and building it accordingly. It is also pertinent in getting buy in as early as possible to ensure teams are engaged when the solution is rolled out.

Backing segmentations with research

Another solution would be to build the segments first and then use research to enhance them with attitudinal values. This solution can work well with one of the benefits of running focus groups to bring life to the segments rather than using the attitudes to drive the segmentation.

Ultimately, it is about finding the right balance that works for your organisation based on wants and needs. Attitudinal segmentations can bring excellent insights but are limited in their applications across a database. Fundamentally, it is a process of ensuring that through engaging the whole organisation, your solution is optimised to meet strategic aims.

How CACI can help

CACI is in a unique position with a UK-wide dataset on all adults, encompassing over 800 variables that we can use to profile and create proxy variables to support the possibility of a successful bridging exercise. We help solve the challenges associated with bridging attitudinal segmentation for leading organisations many times each year.

To learn more about getting the most out of your segmentation and how CACI can support you through this journey, get in touch and we can discuss your challenges in more detail.

Merry Hill is one of the largest regional malls in the UK, encompassing over 200 shops such as major flagships Primark, M&S and Next. Sovereign Centros from CBRE were appointed asset managers of the former Intu asset in 2022, and have since expanded the retail, F&B, and leisure offering, with recent high profile openings including Hollywood Bowl and national debuts for Harvey Norman and XF Gym.

When Merry Hill chose to invest in renovating the M&S flagship store, they needed to quantify the impact changes would have on performance. This required a robust simulation of the future turnover and resulting footfall. In this blog, we uncover the steps that CACI took to help Merry Hill understand the impact of refurbishing M&S and gain investors’ approval to execute it.

How CACI evidenced outcomes of refurbishing Merry Hill’s M&S

CACI compiled a report covering an overview of M&S’ current performance, the impact of a refurbishment on the retailer’s turnover and the cross-shopping potential it could bring across Merry Hill. The report also considered factors such as benchmark centre sales where M&S had already been upgraded, annual trips to Merry Hill should the refurbishment not take place, and potential customer loss to Bullring & Grand Central mall where a new M&S was due to open.

The data sources included in CACI’s report were:

• Transactional Spend Data: Derived from real-world debit card spend data from multiple sources, Transactional Spend Data is a fully consented view of spending patterns. It offers granularity into how different groups interact and how customers engage through an analysis of spend by product category.
• Acorn: CACI’s consumer segmentation model combines geography with a variety of demographics and lifestyle data sources, grouping the entire population into 6 Categories, 18 Groups and 62 Types. It supplies insights into the role that demographics plays in impacting the performance of a location and helps identify key users of a site.
• Location Dynamics: CACI’s machine learning tool predicts the retail, grocery and leisure catchments of over 6,000 destinations in the UK. It considers underlying population and spend, competitive landscapes and accessibility to each destination to model overlapping catchments. In this context, Location Dynamics was used to predict the centre’s performance, and overlap with Birmingham city centre, allowing for a comparison to actual sales to understand where and how the centre could grow turnover.
• Brand Dimensions: CACI’s benchmarking tool tracks the performance of 300 major brands over time. In this instance, it examined M&S spend performance nationally and at benchmarked locations.

What value would refurbishing Merry Hill’s M&S bring?

Having been at Merry Hill for three decades, investing in a refurbishment of M&S would solidify its continued commitment to the centre.

Increase in average spend, dwell time & turnover

CACI uncovered that centres with a refurbished M&S store have seen an increase in average spend per head in benchmark centres by 2.2%, which could help generate a substantial turnover at Merry Hill. With M&S accounting for 11% of centre floorspace at Merry Hill, improving its appearance could impact the ambience of the rest of Merry Hill and contribute to an uplift in dwell time, retail spend, and catering for the wider centre. Refurbishing Merry Hill’s M&S would also accelerate turnover at both the store and across the centre, as refurbishment is cited as a key factor for increasing sales.

Appealing to younger, more affluent demographic

Our research has shown that refurbished stores tend to attract younger, more affluent shoppers. While Merry Hill’s diverse shopper profile of Executive Wealth, Mature Money, and Steady Neighbourhoods Acorn groups is well aligned to key shoppers for M&S, key groups have all under performed versus catchment expectation. A refurbished M&S would appeal to these underperforming visitors.

A reported 82% of M&S shoppers also go on to spend in other stores at Merry Hill. Therefore, the new footfall that a refurbished M&S would attract would benefit other tenants in the centre.

Sales growth from new & existing shoppers

Within this project, we were able to quantify the number of new Merry Hill visitors that would be generated as a result of the refurbished M&S, with considering factors including their potential spend in M&S and their spill-over expenditure across the wider centre.

Graeme Jones, Executive Director at Sovereign Centros from CBRE: “M&S has been a big part of Merry Hill for several decades, so any decision about their future is one that needed to be made with real consideration of the potential impact on the destination. When we decided that we wanted them to introduce their latest shop fit, while consolidating from two units into one to create new opportunities, we started to create a proposal for M&S that would make the best possible case for a significant investment commitment. The data and insight from CACI was a crucial element of that business case, emphasising the rationale from a visitor, brand, and landlord perspective. It helped achieve a positive outcome for all parties, and the new M&S store is already beating commercial targets, and has had a big impact on Merry Hill and its visitor numbers.”

Ellie Brettell, Senior Property Consultant at CACI: “We’re increasingly being asked to support decisions like this one, where significant investment is involved and multiple parties need reassurance that the right choice is being made. Our objective, data-driven approach helps provide that clarity. Our contribution to this fantastic deal for Merry Hill was possible because of our expertise working for brands and owners of places – we understand the goals and potential impacts on both sides and can therefore create a report that rationalises a decision for all parties. Our evidence base made it clear that this deal would create positive outcomes for everyone involved, so naturally we’re proud that our work has helped to deliver such tangible success.”

How CACI can help

The insights provided through CACI’s report instilled both internal and external stakeholders with the necessary confidence to make significant investments in the refurbished M&S. To learn more about our products and data available from key partners to generate a single view of the UK property market, contact us today.

At CACI, we have been supporting charities in optimising their data by supplying ongoing support through solutions, technology, tools and data that work in a more targeted and efficient way and ultimately help more people. Marie Curie, a leading charity dedicated to providing free palliative and end of life care and support to people living with terminal illnesses, has been making significant strides in enhancing its fundraising and supporter engagement strategies. Their work has been raising public awareness and influencing decision-makers across the UK on the issues affecting those reaching the end of their lives and the people closest to them, enabling more people to access high quality care and support when and where they need it most. 

In a recent webinar, we came together to share insights into their collaborative efforts of leveraging data for greater impact. In this blog, I’ll uncover the key takeaways from the webinar and the value of Marie Curie’s work with CACI, combining their own data with CACI’s to improve their supporter engagement and ultimately increase income. 

Building strong data foundations and data enrichment

I kicked off the webinar by emphasising the importance of building strong data foundations, highlighting common challenges faced by charities, such as siloed data and inconsistent supporter information. These challenges hinder the depth of data insights and the unification and linking of data, ultimately impacting improvements for the quality of end-of-life outcomes and gaining a granular view into supporters. By addressing these foundational issues, Marie Curie can better enrich their data and activate it for meaningful engagement. 

Why did Marie Curie embark on a data enrichment journey? 

Mark Lumby, Head of Fundraising Insight at Marie Curie, shared the charity’s motivation for embarking on a data enrichment journey: the necessity of understanding more about their supporters beyond basic demographics. The more data charities have access to, the more robust their engagement strategies can be shaped, resulting in more income from supporters. By partnering with CACI, Marie Curie aimed to gain these deeper, necessary insights into supporter profiles, affluence, interests and behaviours. 

CACI’s Acorn and Ocean data have played a crucial role in Marie Curie’s data enrichment efforts. Acorn is CACI’s powerful consumer classification tool that segments the UK population by postcode, enhancing the charity’s understanding of different types of people and places by analysing demographic data, social factors and behaviours. Ocean is CACI’s consumer database that offers lifestyle variables, further enhancing Marie Curie’s customer understanding through the ability to assess 100 variables that illustrate supporters’ profiles and interests to target them effectively. Together, these tools have enabled the charity to create detailed supporter profiles and uncover new engagement opportunities. 

What were the strategic objectives & key use cases?

Our collaboration with Marie Curie was driven by strategic objectives, including enhancing their product portfolio by identifying overlaps and opportunities for cross-selling. By understanding the profiles of their supporters through a lens enriched by data, Marie Curie could tailor their engagement strategies more effectively by engaging with supporters at individual or segment cohort levels and determine the best methods of interaction via online or offline channels. Through data enrichment, the type of content and messaging could also be crafted to appeal to the target demographic of supporters and personalise their experience.

What has worked well?

Steph Gray from Marie Curie’s insight team shared practical examples of how enriched data has been used to drive value. One notable success was the creation of a profile model for cash appeals, which significantly improved response rates and ROI. By targeting supporters who resembled existing cash donors, the charity improved engagement and secured higher second gift rates. 

Marie Curie’s efforts to cross-sell and acquire new supporters have also benefitted from data enrichment. By identifying key audience groups and tailoring their messaging, the charity has seen improved results in cold acquisition campaigns. This targeted approach has led to more effective use of resources and better overall outcomes. 

What’s next for Marie Curie?

Going forward, the charity plans to continue refining their data models and datasets and explore new variables for up-to-date, accurate supporter understanding. They aim to combine demographic data with behavioural insights to create even more robust supporter profiles, along with additional creative and channel selection testing. This ongoing commitment to data-driven strategies will help Marie Curie maximise their impact and influence supporter journeys.     

Our partnership exemplifies the transformative power of data in the charity sector. By enriching their supporter data and leveraging advanced segmentation tools, the charity has been able to enhance their fundraising efforts and engage supporters more effectively. By watching the webinar here, you can find out how data can drive meaningful change in the charity sector. To learn more about the continuous innovation and strategy refinement Marie Curie is undertaking, visit their Knowledge Hub. 

The direct-to-consumer (DTC) subscription space has experienced remarkable growth in recent years, with brands such as Huel, HelloFresh, Beauty Pie and Whoop becoming household names. The appeal is clear, convenience, personalisation, and a regular stream of products delivered directly to the customer’s door.

But as the market expands, so too does the competition. New brands are launching constantly, each offering their own take on the subscription model. In this crowded space, standing out and staying relevant has never been more important.

One asset continues to distinguish the leaders from the rest: data. And not just any data, but high-quality, well-structured, actionable data, paired with smart analytics and insight-driven strategies. For DTC subscription brands, the ability to understand and act on customer data can be the difference between long-term growth and slow decline.

The data advantage in a competitive market

DTC subscription models naturally generate rich pools of customer data. Every order, preference, skipped delivery or cancellation helps to build a clearer picture of who your customers are and how they behave.

This wealth of data is a significant advantage, but only if it’s properly harnessed. When collected, cleaned and analysed, it can power everything from personalised communications to churn prevention and sustainable growth. Without it, brands are essentially flying blind in a market where insight is everything.

Retention: Knowing your customers, keeping your customers

Retention is the cornerstone of subscription success. Acquiring new customers is just the beginning, keeping them engaged and subscribed is where the real value lies.

But customer loyalty is fragile. Understanding why subscribers leave is critical. According to the 2024 State of Subscription Commerce Industry Outlook,

• 38% of consumers cancel a subscription due to financial pressures,
• 37.9% do so because they no longer want the service, and
• 22.2% say the price is no longer justified.

With this knowledge, brands can adopt a more proactive approach to retention:

• Segment your audience to understand who your loyal advocates are, who is at risk, and who may need re-engaging.
• Predictive analytics can help flag early signs of churn, such as skipped deliveries or changes in usage.
• Personalised re-engagement tactics, based on prior behaviours and preferences — can help win customers back with relevant offers, reminders, or tailored product suggestions.

Retention isn’t just about keeping a customer on a plan — it’s about continuously proving your value in ways that resonate personally.

Personalisation: Meeting customer expectations every step of the way

Today’s consumers expect more than a generic experience. Personalisation has become a baseline requirement. A 2024 Recurly report found that 74% of consumers cite personalisation as one of the top reasons for subscribing.

That means understanding who your customers are, what they care about, and how they want to engage. Personalisation is no longer a “nice to have”, it’s a driver of acquisition, engagement and loyalty.

To personalise effectively, brands must:

• Know which messages resonate with specific customer segments.
• Understand if some groups are more motivated by sustainability, while others care more about value for money.
• Adapt product recommendations and content based on past behaviour and preferences.

When brands show they truly understand their customers, they foster deeper connections — and that translates into longer-term relationships. 

Growth: Finding your next customers

Growth in the subscription space doesn’t mean casting a wide net and hoping for the best. The most successful DTC brands take a targeted approach, using their existing customer data to find lookalike audiences with a high likelihood to convert.

• By profiling your existing customer base, you can uncover the traits, behaviours and preferences that define your best customers.
• These insights allow you to find new audiences that mirror these key characteristics, creating highly efficient acquisition campaigns that target the right people, not just any people.
• Understanding why your customers buy from you also allows you to refine your value proposition, ensuring it’s aligned with what matters most to your target audience.

With rich data and actionable insights, growth becomes more predictable, more efficient and more sustainable.

Aligning with customer values

Modern consumers are increasingly values driven. For many, sustainability is no longer optional, it’s expected. A 2023 survey by Loop Subscriptions found that 73% of consumers are willing to pay more for sustainable products.

For DTC brands, this presents an opportunity to connect more deeply with customers by:

• Highlighting sustainability efforts in communications.
• Offering eco-friendly product options or packaging.
• Tailoring messaging for customers who value ethical practices.

Sustainability isn’t just good for the planet — it’s good for retention.

Data as a competitive edge

In such a fast-moving and competitive sector, the brands that succeed will be those that treat data as a strategic asset, not just an operational by-product.

It’s not just about having data — it’s about ensuring it’s high-quality, well-structured, enriched, and analysed in a way that powers smarter decisions across acquisition, retention and personalisation.

DTC subscription businesses have an inherent data advantage. Those who embrace this, invest in it, and apply the right analytical tools will not only understand their customers better — they’ll also build more engaging experiences, stronger retention strategies and smarter growth plans.

Data isn’t just numbers on a screen — it’s the blueprint for competitive advantage.

Want to discover how your subscription business can turn data into a competitive advantage?

Speak to CACI’s data science experts today — we’ll help you unlock the insights that drive growth.