Capability: Customer Strategy

How brands can start delivering on the promise of ‘real-time’ communications

Posted on: 3 September 2024
How brands can start delivering on the promise of ‘real-time’ communications

Real-time CRM communications are becoming a universal expectation from customers regardless of industry or platform. In fact, 72% of customers expect ‘immediate service’ from the brands they interact with. This can appear daunting for a business that has never considered how to begin serving real-time communications, both in how to enable it, then in how to use it effectively. Before we discuss this, however, we must first dissect the meaning of ‘real-time’.

What are real-time communications and how do they work?

‘Real-time’ refers to the capturing and processing of data. To be able to register a customer behaviour or ‘event’ immediately is a powerful thing – to then use that event to trigger a communication gives customers a sense of responsiveness and targets them when their interest and propensity is likely to be highest.

For this to work, a tracked event must take place, which is then linked to a central customer or user profile. This event will trigger an automated process within your CEP or CRM platform to then deploy a communication to that customer. A couple of examples of this are:

Real-time communications triggered by customer behaviour

There are various customer events that brands will be looking to target through triggered communications. One of the most common examples of these is an abandon basket campaign – if a customer began a purchase journey but fell out of that journey without completing it, brands can target them immediately with a prompt to finish their order while the purchase intent is still there.

Real-time dynamic messaging based on customer attributes

Depending on certain customer attributes, customers can also be served dynamic content based on what we know about them prior to starting a new web or app session. If we imagine a customer that may have purchased from a brand once, but then not returned within a certain number of months, it is possible to welcome them with a communication that recognises that and potentially incentivises them to purchase again upon starting their new session (for example – ‘Welcome back, here’s 5% off!’).

In both examples, a brand would need to tie the app or web session to a particular customer, have an event set up to register ‘basket additions that did not result in a sale’ or ‘return visits over ‘x’ months’, and to pass this information through to a chosen CRM platform to trigger an automated communication. Both are powerful use cases that demonstrate the potential value that can be unlocked through the real-time capturing and processing of data.

How CACI can help

CACI’s experts have extensive experience in helping brands start their journeys into real-time communications, from the initial identification of the right use-cases (as above) to identifying the right enablers across data and technology to make it happen.

In doing so, enabling real-time communication can be an incremental process, where use cases are tested and evaluated for their value and built upon steadily, eventually leading to a fully connected data ecosystem with more complex real-time strategies.

To see how CACI can help you begin planning your real-time strategy, contact us today.

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Why should businesses utilise the latest LLMs and latest NLP techniques?

Posted on: 30 August 2024
Why should businesses utilise the latest LLMs and latest NLP techniques?

In our rapidly evolving world, leveraging cutting-edge technologies is no longer a luxury, but a necessity, and Natural Language Processing (NLP) stands out as one of the most transformative tools available. NLP focuses on the interaction between computers and human language, this is commonly seen in systems such as Large Language Models (LLMs), Interactive Voice Response systems (IVRs), and voice assistants. These technologies have the power to revolutionise a company’s service by making interactions more efficient and effective, whilst reducing costs, so why haven’t more companies harnessed them? 

Let’s consider customer service – an area where the technology has already made significant strides. Many businesses still have systems that heavily rely on human operators, requiring them to tackle customer calls with highly specific and complex issues. Implementing new NLP systems can lessen the reliance on these human operators, leading to decreased wait-times, improved efficiency, and 24/7 availability. However, these systems often come with significant costs and require substantial infrastructure changes. If not executed properly, they can lead to unintended consequences and ruin the customer experience. Therefore, before adding new systems, you must understand and quantify why customers are contacting you and identify where systems can enhance the customer journey and reduce cost.  

What AI tools are there for text analysis

Various AI approaches are available to address a wide range of problems. We can categorise them as follows: 

  • Generative LLMs: Examples include GPT-4 (ChatGPT), Gemini, and Claude. These are the models that excel at generating content e.g. summarising a customer call.
  • Non-generative LLMs such as BERT, RoBERTa and their various forms: These models are used extensively in applications that require deep understanding of context or meaning e.g. accurately classifying known topics for a customer call.
  • Traditional NLP techniques: This category encompasses rule-based systems, Word2Vec, and more. They work well with simpler tasks. E.g. detecting if a particular service is mentioned in a customer webchat.

What’s the difference between generative and non-generative LLMs?

Fundamentally, LLMs like GPT-4 and BERT are built from the same building blocks called transformers, so what makes them differ?

Typically, a transformer is comprised of both Encoder and Decoder parts, but it’s been found that models can be specialised through stacking either encoder or decoder blocks. GPT-4, a generative LLM, is often referred to as a decoder-only architecture. This allows the model to receive an input, then generate text that is contextually relevant to the input. Not only does it mimic human-like text, but these responses can also be seemingly creative.

BERT, on the other hand, is built using encoder-only architecture, so think of it as a specialist in both reading and interpreting human language, rather than generating it. Non-generative LLMs, when utilised effectively, offer considerable power without a lot of the overheads associated with the generative LLMs. While some infrastructure is necessary for their implementation, the costs are not prohibitively high, especially when employing distilled models. For instance, users can avoid making expensive high frequency API calls to generative LLMs or using extensive computational resources. Additionally, users have greater control over model customisation, allowing them to achieve optimal performance for domain-specific tasks. These advantages make non-generative LLMs an excellent choice for handling highly sensitive data within a secure, isolated system e.g. a client’s secure inhouse database and system.

The following table offers a high-level comparison of the different NLP tools:

Are traditional NLP techniques still relevant? 

Although LLMs are highly adaptable and have great performance across a wide-range of tasks, traditional NLP techniques remain relevant due to their task-specific tunability. These methods have been in use for decades and continue to play a crucial role in various niche applications. Traditional approaches often benefit from cost-effective compute resources and specificity, but they require more manual tuning to achieve optimal results, and typically only work well on low-complexity tasks. In general, these techniques are better-suited for curated, lower-performance internal systems, where they can carry-out dedicated automated tasks inside a pipeline.

Intent classification in action 

Back to our customer service example – using a combination of NLP techniques, generative, and non-generative LLMs, we can identify the intent of customers when speaking to customer service operators. 

In the first instance, we can apply quick traditional NLP methods to identify if this alone is suitable for our task. However, due to the complexity of customer interactions, it is unlikely that this will produce robust results. The next step would be to employ a generative LLM on a subset of calls to identify intent topics. While this may provide sufficient insights to enhance the customer journey, for truly informed business decisions, it is essential to gain a holistic understanding. Therefore, quantifying the number of calls related to each topic might be of interest.  

To quantify the number of calls it is best to use a non-generative LLM like BERT, as they will outperform their generative counter parts, are much cheaper and far easier to implement at scale. Previously we have had great results using these types of techniques and methodologies in a range of different projects.

How CACI can help

If you’re looking to enhance your business with cutting-edge NLP solutions, our in-house data science teams are here to help. Contact us today to start transforming your use of data and stay ahead in the ever-evolving landscape of AI and data science.

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Connecting paid media to first-party data: a path to enhanced customer engagement

Posted on: 29 July 2024
Connecting paid media to first-party data: a path to enhanced customer engagement

In today’s competitive market, the cost of acquiring new customers is continuously increasing. Coupled with changing privacy regulations and consumers’ growing demands for personalised experiences, traditional acquisition strategies that are heavily reliant on third-party data are becoming less effective. Herein lies the crucial role of first-party data in acquiring the right customers and effectively retaining them.

Getting started: why alignment and collaboration matters

Realising the potential value of first-party data requires effective collaboration between Paid Media and CRM teams. When these teams operate in silos, valuable customer insights and behavioural data are not shared effectively, and brands risk a disjointed experience alongside increased ad spend.

Aligning these teams around cohesive goals and strategies ensures that the rich, actionable insights derived from first-party data are used to inform and optimise paid media campaigns. This cross-team collaboration can significantly enhance targeting accuracy, message relevance, and ultimately, customer acquisition and retention.

Unlocking the value of first-party data across CRM and social

When it comes to delivering impactful CRM campaigns, particularly on highly competitive social channels, first-party data is invaluable to delivering a relevant and cohesive customer experience. By implementing the following, brands can ensure the effective and impactful utilisation of their data:

  1. Comprehensive customer profiles: By integrating data from various touchpoints—such as website interactions, purchase history, and email engagement—brands can build rich and comprehensive customer profiles. These profiles enable precise segmentation and targeting, allowing for highly personalised ad content that resonates with specific audience segments to come to fruition.
  2. Behavioural targeting: First-party data can be used to understand customer behaviours and preferences. For instance, if a customer frequently browses certain product categories but hasn’t made a purchase, targeted ads featuring those products, along with special offers or discounts, can be highly effective in driving conversions.
  3. Dynamic and personalised content: Social media platforms offer advanced tools for dynamic ad content. Brands can use first-party data to create ads that dynamically change based on the viewer’s profile and past interactions. Therefore, creating personalised and distinctive comms at key customer moments not only increases engagement, but also adds a competitive advantage through an enhanced overall customer experience.
  4. Cross-channel consistency: Ensure that the customer experience is consistent across all channels. If a customer has already purchased a product, avoid retargeting them with the same product ads. Instead, use the opportunity to introduce complementary products or services, thereby adding value and enhancing the customer journey.
  5. Real-time optimisation: Leverage real-time data to continuously optimise campaigns. Monitor customer interactions and campaign performance closely, and use these insights to make timely adjustments to your targeting and messaging strategies.

How CACI can help

In the context of rising customer acquisition costs, the alignment and collaboration between paid media teams and CRM teams have never been more critical. This strategic integration not only enhances the customer experience, but also drives better business outcomes—improving acquisition efficiency, increasing customer loyalty, and ultimately, boosting the bottom line.

As the digital marketing landscape continues to evolve, brands that prioritise the seamless integration of their marketing efforts and harness the power of first-party data will be best positioned to succeed. The future of marketing lies in breaking down silos and fostering collaboration, ensuring that every customer interaction is informed, intentional, and impactful.

CACI’s team of experts have extensive experience in helping clients enhance customer engagement through a multitude of strategies and solutions. If you or your business are ready to explore how first-party data can lead to effective customer acquisition and retention, please get in touch to discuss how we can help you.

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How to estimate affluence with satellite imagery

Posted on: 19 July 2024
How to estimate affluence with satellite imagery

When looking to understand the geodemographics of a country, a segmentation can be an invaluable tool for describing the differences between neighbourhoods to drive decision making, guiding you towards the areas where your customers or lookalikes are. Indeed, CACI’s Acorn helps thousands of organisations better understand and target their audiences within the UK market. One of the key ways Acorn differentiates between top-level Categories is by affluence, which is a crucial factor for a segmentation in a business context. 

In the UK, there is a wealth of data we can draw upon to build geodemographic segmentations like Acorn, including a robust and detailed census, land registry, and most importantly, a well-defined, small-scale Postcode system. But in foreign markets, such detailed data often doesn’t exist, and where it does, it can be of poor quality, hard to verify and at a regional level. So, how can we build a reliable segmentation in these markets? 

Satellite imagery as a novel approach

In many countries, the nuances in affluence between neighbourhoods can be gleaned not from looking at tables of data, but by looking at them from above. Satellite imagery is incredibly useful when traditional data sources are lacking, but visual differences between affluence levels are clear. Take, for example, the below images of two areas in a desert country: 

In the image on the left, there are large buildings, geometrically defined roads, pools and greenery, which is expensive to maintain in a desert country. This area is likely to be of a generally higher affluence. In the image on the right, there are buildings of uneven height, densely packed together along uneven and jagged roads. This area is likely to be of a generally lower affluence compared to the image on the left. 

We can see by eye the differences between these areas, but we can’t feasibly label all the areas of a country manually. So, how to do we do this programmatically? 

Enter Convolutional Neural Networks (CNNs), a well-established deep learning technique that’s the bedrock of image analysis. Inspired by the visual cortex of an animal, they are trained to identify the patterns and shapes in an image and use this to predict the likely classification of objects or the image as a whole.  

For successful usage of a CNN, however, quality training data is vital. In classic examples of image recognition, such as the MNIST dataset of handwritten digits, most people would have no issue labelling the training images correctly to feed to the model. This is trickier for labelling the affluence of a small area, though, as you need deep local knowledge and the time to manually label thousands of images to achieve a model with usable accuracy. CACI has invested heavily in building a robust pipeline for this process, allowing us to achieve the scale required for accurate modelling. 

H3: The unifying geography

We now have a methodology for generating some information about affluence, but we still have another problem to tackle – what geography should a segmentation be built at? 

The natural response might be to consider administrative boundaries. This is the level at which most governmental social and economic data is released, so it makes sense to consider this as an option. However, the irregularity of the shape and size of administrative regions in many countries means that it can be hard to compare areas like-for-like, hampering effective decision making. 

H3 – a geospatial indexing system developed at Uber – splits the globe into a grid of tessellated hexagons at varying scales, from the largest scale at 110 hexagons to the smallest at ~570 trillion hexagons. It’s gained popularity thanks to its ease of use, speed and availability of algorithms and optimisations for working in its geography. 

H3 is a great alternative to Postcodes in areas where they can’t feasibly be used. It can be applied consistently across a country and at a low level of granularity, meaning that any segmentation applied at this level can clearly show the differences between areas in an accurate way. It’s also easy to aggregate up to other geographies, allowing you to integrate the data into other systems where data is not so granular. 

How CACI can help

Combining the power of H3 hexagon geography with the information gained from analysing satellite images, we can gain great insight into the relative wealth of areas in countries where existing data is simply not available. 

The ability to apply image analysis, however, means nothing without deep expertise in segmentation and location strategy. By combining your knowledge of your customers with our expertise in data science, insight and location, CACI can support you in your journey. 

Whether you’re an established international organisation or looking to move into a new market, contact us today to find out how we can help you take the next step in achieving your goals.

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Get ahead with CACI: Unlock the power of AI and ML in your CRM

Posted on: 19 June 2024
Get ahead with CACI: Unlock the power of AI and ML in your CRM

Setting the stage:  

The field of Machine learning and AI has evolved rapidly in the last few years, especially in fields where large quantities of data and quick response times to queries are crucial. But given lots of these techniques and methods have been around for a much longer period, why has it taken so long for other industries outside of small start-ups and ambitious tech giants to leverage these methods in similar ways? 

CRM is an essential component of any company’s strategy. The ability to communicate with and understand customers is more important than ever due to the low barriers to entry in highly competitive global markets. Companies have only brief moments to convince customers that they are the right choice for shopping, spending time, or engaging. Optimising these initial and subsequent contacts is paramount to success. 

Beyond just expanding your customer base and attracting new clients, CRM is vital for any company’s retention strategy. The most advanced cutting-edge models in the world are utterly useless if we don’t know how to activate and capitalize on the value they represent. 

ML Foundation:  

In the CRM space our main goals are increasing consumer retention or spend, and we do this via figuring out the most effective ways to communicate with people. This can be broken down into when to speak to them, how to speak to them and why to speak to them.  

Recommendation engines lie at the core of many of these architectures, models that are designed to figure out what you want before you even know you want it. Broadly they work by looking at the kind of customer you are, then at customers like you, then finding things that they’ve bought recently that you haven’t.  

You can even simplify this down into just looking for customers who have an identical purchase history to you. Maybe a laptop you can buy on Amazon doesn’t come with a charger, so commonly when people buy this laptop their next purchase is a charger!! (You can often see this simple logic in the “People also bought” section of Amazon). But even these simple implementations are incredibly powerful in some ways, an educated guess is always going to be better than a random one. 

So how do these methods relate to CRM? Well, the general structure can be pulled away and applied to any subject. When we think about how to engage with a customer, we’re going to look for ways we engaged with similar customers and how these performed. The customer who likes Sabrina Carpenter will probably need to be spoken to in a different way to the Motorhead fan. 

This is simple stuff, right? Well exactly, but it’s a method to show that the underlying AI processes in these platforms aren’t really all that complicated – there’s a lot of room for improvement especially when implementing bespoke solutions with larger data sets.  

The next (generative) step:  

So, we already have ML methods that can tell us when and why to talk to people, great! But what’s the next step? 

All that’s left of our final stage is how to talk to them and what to say, stages which can and are currently being revolutionised by the advent of enterprise grade Generative AI. 

A current pipeline for devising CRM processes may involve creating template communications that are then populated with more specific information, for example customers in a certain segment defined by age and tenure are assigned one template and differing segments are shown another. 

This approach can be time consuming if it needs to be completed for each campaign, and may miss a level of personalisation that people will respond to, feeling as though each message is tailored to them rather than being an email blast they just happen to be caught up in. 

Skilled AI engineers armed with LLM’s can create a unique voice for each consumer, ensuring that quite literally all communication they will ever receive are exactly personalised to them and their engagement habits with your brand. 

Imagine attempting this even a few years ago, assigning a team of people to trawl through millions if not billions of rows of data to ensure that each customer got the perfect messaging for them would have been completely impossible. 

In practice this level of granularity in communications is probably unnecessary but it speaks to the potential these models have in this space – the sky truly is the limit. 

Even starting off small with these steps, giving a small part of a communication a generative component, allowing for large scale A/B testing and continuous model training, the effectiveness of these comms will improve over time. 

Freeing this time up from your CRM team will give them more time to tackle more involved problems that can’t be automated. 

How can we help you on this journey?

Don’t get left behind. Partner with CACI and our experienced in-house data science teams to integrate cutting-edge ML and AI into your CRM processes and experience unparalleled growth and customer satisfaction. Contact us today to learn how we can help you stay ahead of the curve.

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How Estée Lauder harness the “beauty of data” to transform their customer experience

Posted on: 5 March 2024
How Estée Lauder harness the “beauty of data” to transform their customer experience

At our annual Innovate & Accelerate conference, Daniel Lindsay, CRM, Data, Insights and Analytics Director at Estée Lauder, shared the business’ optimal pairing of data and magic behind beauty to enable their enterprise data transformation, taking the retailer from insight to instinct in order to personalise consumer experiences. This winning combination has contributed to the success of their brand value proposition, narrative and positioning through campaigns that struck a chord with consumers.

But how did Estée Lauder decide when the right time for data transformation was? What tools and strategies did they lean on to achieve this, and what were the results?

Why it was time for a big data transformation

Three years ago, Estée Lauder faced various evolutionary periods of marketing, from digital to connected media in terms of consumer interaction followed by the tailored messaging capabilities that came with leaning into data-led media and marketing , particularly first-party consumer data. The business was keen to ensure all their consumers were involved in their journey of change.

According to Daniel: “Our job as a leading beauty company in the UK is to evoke trust from the customer.” Consumers purchase from brands that they trust with their most personal spaces, so ensuring customers are at the root of the brand and understood as granularly as data personalisation allows for is vital. Estée Lauder quickly realised that connecting data to the personalised user experience would give them the competitive edge that they needed to remain an industry leader.

Challenges experienced when working on data transformation & how they were mitigated

Three years down the line of their data transformation, Estée Lauder has faced its fair share of challenges:

  • Heavily investing in consumer data. The business quickly realised their initial consumer data investments were conducted on outdated infrastructure, which complicated their ability to locate their target customer and get a unified view of them.
  • Effectively delivering analytics or insights that would drive fast action and improve accessibility. They had also outgrown their campaign management system, sparking a new consideration of ensuring whatever was brought into the business would connect consumers across the channels.
  • Upskilling and bolstering their in-house capability. This would enable enhanced futureproofing and strategic planning while also upkeeping resources.

Implementing CDP & campaign management tools

To tackle these challenges, Estée Lauder worked with CACI on implementing a customer data platform (CDP) workstream and an innovative campaign management tool, Braze. They also created a new access point for consumer data for quicker decision-making and initiated a change management piece to better plan for the future, with CACI’s support on refining in-house skills.

Working with CACI enhanced the business’ understanding of how their consumers shop across their portfolio of brands. The resulting data was released into Braze, and has more recently been added into Google, Meta and TikTok to take their understanding of consumer data to a new level.

The business’ value realisation through Braze was being able to engage with consumers and make their CRM channels the fastest growing traffic channel across all their direct to consumer (D2C) channels so far. They were also able to increase their key loyalty metrics by 16% in repeat and retention rates across all brands. This was demonstrated through one brand, Aveda, that despite a complex route to market journey, proved that having the right infrastructure in place enabled the business to successfully understand and track consumer points through email or SMS, which has been transformational for the business.

Data transformation in real-time: MAC Cosmetics case studies

Creating Black Friday success for MAC Cosmetics

Elena Hughes, Customer Strategist at CACI, elaborated on CACI’s support with the design and implementation of Braze in Estée Lauder, and its impact on the business’ strategic communications plan ahead of their peak period, Black Friday. This was a commercially critical time in the business’ calendar with a predicted high revenue generation, meaning that the business’ strategy had to be airtight.

To execute this, Estée Lauder assessed the data with CACI to understand how customers behave during peak promotional periods. This resulted in the emergence of four key customer groups:

  • Gifters
  • Price-driven audience
  • Loyal
  • Lapsed (one-off)

The strategy needed to take a segmented approach to tailor the messaging to these specific audiences, which enabled newfound opportunities for creative enhancements as well. As a result, the business noticed a 23% increase in trading performance post-implementation of the strategy, proving the campaign’s effectiveness despite an obvious time crunch and key information presented for access in the most suitable way of actionable insight.

Activating a triggered lifecycle programme at MAC Cosmetics

Replenishment, automated trigger and cross-sale messaging were critical components of the business’ triggered lifecycle programme. Their Black Friday campaign success came from distilling a multitude of strategy-shaping data points.

Learning lessons towards achieving data transformation

Despite maintaining relatively stable sales around Black Friday, CACI’s Cost of Living and purchasing data proved to be crucial to Estée Lauder’s success. While the business noticed that some of the more luxury products like serums declined in sales, the resulting data showed that the “lipstick effect” prevailed and that customers still want to feel good about themselves no matter the economic circumstances, demonstrated in the purchasing of what consumers consider to be essential products.

The business is now equipped with the necessary data to enter peak shopping periods and continue developing efficiencies and creative assets that resonate with customers.

How CACI can help

If you or your business are looking to accelerate customer data or technology changes by connecting and activating your insight, please get in touch to discuss what strategies and solutions that our team of experts can help you deliver.

Uncovering consumers’ leisure priorities in the festive period

Posted on: 13 December 2023
Uncovering consumers’ leisure priorities in the festive period

The latest findings from our Cost of Living consumer survey are in, and we’re taking a look at the insights through the lens of the leisure industry. 

With over 2,000 respondents surveyed in November, we asked consumers about their thoughts and priorities in the lead up to Christmas to help brands understand how their customers may be behaving. For companies in the leisure space, being able to predict the movements, intentions and spending patterns of customers is key at this time of year, especially in the current economic climate. 

So, what did we find? 

Nearly half of consumers still want to socialise and spend despite the impact of the Cost of Living

With 46% of respondents agreeing that the increased Cost of Living will not impact their intended Christmas social plans (up from 40% in 2022), leisure brands can expect to benefit from people wanting to attend and spend on events out of the home this year. 

While this is reflected in general financial fears dropping since the late summer, there seems to be a generational divide with Gen X, Millennials and Boomers feeling more confident. Gen Z, on the other hand, reached a new peak of concern at over 50%. 

Their concerns relate to their personal finances as opposed to family finances or the national/global economy, which could affect brands reliant on young adults to boost their seasonal profits. 

Energy fears remain high as the cold moves in, leading to potential cost-cutting in other areas for some groups

With energy costs becoming more of a focus as temperatures drop, some demographic groups are having to cut down on other costs to keep warm this winter – with one in three among the Low Income Living Acorn category expecting to have to do so. 

The impact decreases as we climb the affluence scale but remains fairly significant, with over 20% of the Established Affluence category also considering cost cutting for this reason. 

Spending on food and drink at home remains a priority, but the importance of entertainment and leisure at Christmas is growing

With a significant 79% of people considering spending on food and drink at home to be important this festive period, there is further optimism for the leisure industry as our latest survey has also detected a shift back towards entertainment and leisure as a source of importance. 

While consumers report that most other areas of spending are reducing in importance, entertainment and leisure is trending in the other direction, with 59% of consumers surveyed classifying entertainment and leisure as either somewhat or very important to them this year, which is up from 53% in 2022. This is supported by 47% of respondents identifying that socialising outside of their homes this year is important, which is a slight increase from 2022. 

Overall, the social planning picture is a lot less negative than last year

When we consider the contrast between pre-pandemic and Cost of Living crisis behaviours versus consumer attitudes now, it’s fair to say that people continue to exert caution in the lead up to Christmas. Nonetheless, we’re seeing less negativity year-on-year, which shows that there’s opportunity for leisure brands in the coming weeks. 

Brands may still want to consider how different demographic groups are going to drive success this Christmas, as levels of concern and caution seem to be directly related to affluence. The findings show that the Established Affluence category appear to place the most importance on maintaining their food and beverage spending and socialising this year. 

When taking age into account, we found that a surprisingly large pocket of younger respondents actually prefer New Year’s Eve to Christmas Day as a celebration. So, this could be something to consider when rolling out engagement strategies post-Christmas. 

Apply these insights to your consumers and stay in the loop as you strategise

We work with a range of market-leading brands in the leisure industry, helping them to identify, understand and locate their customer base to drive value for their businesses and inform successful estate optimisation and growth. If any of our demographic or location-focused data is of interest to you, or if you’d like to dive deeper into our survey results, please get in touch to discuss this with us. 

Travel spend behaviours that will redefine your customer strategies

Posted on: 3 November 2023
Travel spend behaviours that will redefine your customer strategies

travelling

In our previous blog, we explored some of the most common challenges that have arisen in the travel sector in 2023 and how you can leverage digital marketing and personalisation to tackle them. 

In an era where the Cost of Living is placing pressure on consumers’ budgets, the significance of precise, targeted marketing and aligned messaging cannot be overstated. Moving towards the end of the year and the holiday-booking surge that happens in January, marketers will need to be aware of timely shifts in behaviour and expectations to capitalise on customer intent at the right times. 

Through our recent Cost of Living consumer survey, we have identified important shifts in travel spending habits that will influence the January booking window, and have pinpointed the demographic groups experiencing the most significant adjustments:

  • Travellers are more frugal than they were, but still want the best experience they can afford 
  • Travellers will spend more time than usual researching to try and find the best the value options
  • Travellers may be more sceptical about convenient booking options and package deals still offering the best available value 
  • Solo travellers, travellers without children and families are all being hit differently, and will therefore have different needs and expectations when it comes to researching and booking.

Despite these shifts, there are still plenty of opportunities for travel businesses to keep customers interested in going away. Below we have detailed some of the tactics that can help:

Consumers’ travel spending will continue—with exceptions

Many travellers may have set expectations in their minds around what a ‘good trip’ looks like, such as having to be a certain distance away or for a minimum number of days. Our findings concluded that despite the ongoing Cost of Living crisis, holidays remain a priority for consumers of all ages, and they are determined to find ways to make them happen.  

In fact, 57% of consumers surveyed have or will be making changes to their holiday habits to save money and get more for their money. 

Respondents expect to cut their expenditure on their next holiday, with 45% saying they will either find a cheaper destination, travel option, accommodation, do fewer activities or simply reduce their trip length. Which means that they will most likely spend more time researching their holidays and trips. Equally, this may affect the package holiday market as consumers compose their own holidays by booking their own flights, hotels and transfers.

The most affluent Acorn demographic groups expect to cut their holiday expenditure in this way more than other groups, as do millennials and Gen Z respondents. 22% of respondents are also taking fewer breaks compared to previous years.  

To continue to encourage travellers to go away, travel businesses will need to shift the focus from larger packages and holidays and instead start spotlighting the benefits of closer destinations and shorter trips or weekend getaways. Their focus language will need to be around ‘doing more with less’ to ensure travellers continue to see the value in getting away no matter the length of holiday. Travel businesses can promote this throughout the year as well, as shorter breaks are far more flexible and can happen at any time.

Gen Z are spending the least on travel this year

Younger holidaymakers—particularly Gen Z— appear to want to spend as little as possible to keep travelling this year.  

When it comes to cheaper destinations and accommodation, more than 1 in 5 respondents of younger age groups have opted for these. Younger men surveyed are particularly determined to continue to take breaks as they have before. Just 14% of Gen Z men expect to take fewer breaks compared with previous years, yet that rate more than doubles among Gen Z women, 29% of whom reported that expectation.  

To combat this, travel businesses that speak directly to traveller concerns around value will build their trust in the options they’re being presented with. For travellers that are wary of costs and will expect to be researching for longer periods of time to seek the best value, curated options and direct, value-based messaging will help to make their concerns feel acknowledged and will offer a faster and more convenient option for them to browse.

Family holidays are being cut…

Respondents that have children appear to be affected to a greater extent than those without. The appeal of cheaper destinations rises from 14% among those without children to 24% among those with under 18s in their household. Bearing this in mind, more price-sensitive families can be a stronger focus for value-based messaging and cheaper travel options from travel businesses.

…while solo travellers are on the rise

The results show that independently living, single travellers are taking the most advantage of getting away on holiday this year. In fact, rates of those cutting back on holiday expenditure are nearly 1/3 lower among those who live alone. This includes reducing spend in other areas to make room for travel and shortening the length of trips compared to previous years. To maintain interest across all pricing options, travel businesses should target more expensive and premium options towards solo and non-children couples.  

How can CACI help?

As a trusted partner to major brands within the travel industry, our team is highly experienced in supporting strategic targeting by leveraging the necessary data and technology to understand customers and their behaviours as innately as possible and being able to design marketing strategies to target these groups. 

CACI partners with global brands to harness and enhance customer data, enabling them to identify and prioritise the most valuable customers. Insights are then activated through strategic CRM initiatives and acquisition strategies, ensuring targeting is precise and relevant. This approach is pivotal for brands seeking to align their products with consumer needs and foster long-lasting brand loyalty, repeat bookings and maximising share of wallet. 

To find out how we can support your business strategies or operations by enhancing your customer understanding, or to find out more about the products and services we offer, please get in touch. 

Read blog 1 from our travel series: Travel sector hurdles and the promise of digital marketing and personalisation

Travel sector hurdles and the promise of digital marketing and personalisation

Posted on: 9 October 2023
Travel sector hurdles and the promise of digital marketing and personalisation

The travel sector has faced turbulence over the past few years. From the devastating impact of the COVID-19 pandemic, to the cost of living crisis and ever-changing travel norms, the sector finds itself navigating a host of challenges.  

A holiday purchase is often one of the largest purchases that a family will make in a year, with an average UK family spending roughly £4,000 per annum. With ever-inflating costs and even higher customer expectations, providing an exceptional customer experience is critical to your long-term success. 

In this blog series for the travel sector, we will be exploring how you can harness the power of data and modern marketing technology capabilities to overcome and even exploit these challenges. 

What are the most common issues in the travel sector in 2023?

Changed travel behaviour

The aftermath of the COVID-19 pandemic and the cost of living crisis have left their mark on the travel sector. Travellers are more cautious, often opting for cheaper domestic or localised trips over international adventures. Health and safety have become paramount, leading to a new set of expectations from travel providers.  

In fact, 25–34-year-olds were reluctant to make holiday plans this year, instead waiting to see how the cost of living crisis evolved. 

Moreover, ¼ of those aged 55+ made no plans to travel this year. 

With different demographic groups approaching their holiday planning in different ways, applying the right segmentation techniques to target those who are most likely to travel is crucial. 

Environmental concerns

There’s also a growing call for sustainable travel. Tourists and travellers are more eco-conscious than ever, wanting to reduce their carbon footprint and seeking eco-friendly options. The consideration of travelling sustainably is especially a factor for 18–24-year-olds, where 22% say this is important to them. 

Over-tourism

Popular destinations from Venice to Bali faced issues of over-tourism, where local ecosystems and infrastructures have become overwhelmed. 

Complex travel policies

With countries having their own quarantine measures, vaccine mandates and travel advisories, there’s an increasing complexity in international travel logistics. 

Trust deficit

After numerous flight cancellations (UK flight cancellations are up 39% in 2023!), changing regulations, strike disruptions and refund issues during peak pandemic times, travellers are more sceptical about committing to bookings.

How can digital marketing & personalisation save the travel sector?

Digital marketing and personalisation have emerged as two tools that can address several of these issues: 

Tailored travel options

Through advanced AI and lifestyle and behavioural data analytics, travel companies can now provide tailored packages and ancillaries for individuals. If a user has shown interest in eco-friendly destinations or prefers secluded spots, personalisation and decisioning tools can offer suggestions accordingly. This not only enhances user experience, but can also divert traffic from over-crowded tourist spots. 

Building trust through transparency

Customer Experience Platforms (CEPs) like Adobe Journey Optimiser and Braze can provide customers with real-time updates on disruption, travel policies, health and safety measures and reviews. An informed traveller is a happier traveller. That happiness will lead to greater trust, and an increased likelihood of future bookings. 

  • Educative marketing:  Digital and content-rich campaigns focused on educating tourists about the importance of sustainable travel can be instrumental. From tips on how to be a responsible traveller to highlighting the less-explored destinations, digital content can shape travel behaviours. It’s worth noting that according to our recent Cost of Living consumer survey, 17% of people believe that they will do most of their travel via sustainable methods by 2030.
  • Feedback mechanisms: Personalised feedback options and rapid data ingestion help companies understand the unique needs of each traveller, leading to improved offerings around ancillaries, personalised and targeted to the right customers via mobile channels, making holiday purchases easier. 
  • Loyalty programmes & retargeting: CDPs and data-driven marketing allows travel companies to launch personalised loyalty programmes. With retargeting strategies, companies can re-engage potential customers, offering them custom deals based on their search and booking history. 

Despite the many challenges faced by the travel sector in 2023, the digital and data tech revolution offers an array of solutions. By adopting well-planned digital marketing and data-driven personalisation, the sector can not only provide enhanced customer experiences, but also address broader issues such as over-tourism and environmental concerns. It’s a transformative era, and travel companies at the forefront of these digital innovations are poised to chart a smoother course ahead. 

How can CACI help?

CACI is already a trusted partner to major brands within the travel industry, developing strategic customer journeys to increase frequency of bookings and ancillaries’ revenue through the effective use of data, technology and targeted marketing. 

If you would like to discuss your needs in any of these areas, or to find out more about the products and services we offer, please get in touch.

 

Read blog 2 from our travel series: Travel spend behaviours that will redefine your customer strategies

Using CDP to design a successful business operating model

Posted on: 3 October 2023
Using CDP to design a successful business operating model

In our last post, we shared some tips for a successful CDP implementation. In this post, we focus on one of the most critical factors for CDP success: designing a new business operating model. If you’d like to read all the blogs right away, you can register here to access the complete series.

We often find that organisations try to solve their marketing challenges by only changing their data and tech capabilities. However, people and process changes alongside this are just as important.

With the introduction of a CDP, businesses gain access to different capabilities that enable greater automation and efficiencies. The challenge lies in how to best adopt the use of these new capabilities, especially when an organisation currently consists of multiple teams, each responsible for different channels, life stages, products or customer segments.

A new operating model is needed to redesign and reorganise these teams, ensuring that processes are designed with the new capabilities in mind. This ensures that the organisation fully benefits from its capabilities.

Without a well-designed operating model, businesses may fail to harness the full potential that a CDP has to offer. In this blog, we will discuss the best practices for designing a new business operating model to get success from a CDP implementation.

Step 1: Conduct a business-wide assessment of the existing operating model

A business-wide assessment covering a review of the existing operating model is a good place to start. This will help identify gaps and inefficiencies that need to be addressed before implementing a CDP. These gaps may be related to skills as well as the actual number of resources required by various functions.

Step 2: Establish design principles

Next, establish CDP operating model design principles that will guide the development of the target model. This will ensure that the CDP capabilities are utilised efficiently and effectively. When designing the target operating model, consideration needs to be given to the re-allocation of resources and the impact on individuals whose jobs will likely change. Ideally, the new operating model will enable them to work more effectively and efficiently. However, any change needs careful consideration and planning ahead of roll out.

Step 3: Get the necessary buy-in from stakeholders

A step-by-step approach will ensure success. It is important to get buy-in from leadership to ensure that everyone is aligned and invested in the project. This will help to ensure that communication, process and people collaboration are effectively managed. A steering committee is necessary and plays a vital role in the design of the operating model and the management of delivery. Within that, having CDP advocates who will champion the new operating model will help drive adoption across the organisation.

Overarching best practices to consider

When designing the target operating model, it is important to balance rigour with flexibility. A CDP implementation should account for the impacts on different parts of the business in different ways, from reducing the burden on data engineers to empowering marketers to deliver real-time use cases. This requires a collaborative effort between teams and a willingness to adapt to new ways of working.

Ultimately, designing a new business operating model is critical to the success of a CDP implementation. By taking a step-by-step approach, establishing CDP advocates and balancing rigour with flexibility, businesses can maximise the value of their CDP investment and gain a deeper understanding of their customers. The key consideration of change a CDP brings such as communication, process, people collaboration, and the need for leadership buy-in make it clear that CDP success is not just about data and marketing technology.

How can CACI help?

As subject matter experts at CACI, we can tell you that a well-implemented CDP can be a game-changer for businesses of all sizes and we have hands on experience with many brands including ASOS, Kingfisher, L&G, PlayStation, Telegraph, EasyJet and DFS.  If you’re interested in learning more about CDPs and how they can help your business, please don’t hesitate to reach out to one of our experts.

This post is the part of a blog series on all things CDP, so make sure to check out our previous blogs to get a complete picture of CDP implementation best practices. If you would like to download the whole blog series, you can simply register here to download a copy of the whitepaper.

If you’re interested in learning more about CDPs and how they can help your business, please don’t hesitate to contact us and reach out to one of our experts.

Continue reading:

Blog 1 – How a CDP can transform your customer experience architecture

Blog 2 – CDP vs. SCV: why choosing between the two is a big mistake

Blog 3 – CDP and CEP: A perfect pair for a seamless customer experience

Blog 4 – How to avoid pitfalls & drive results in CDP implementation