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Falling Bricks: Retail disaster movie coming to a town near you?

28th Nov, 2011 by Ian Thurman

 
 

Ian Thurman, Vice President, Location Planning

TIME FOR HARD HATS?

As even the mighty M&S struggle to achieve sales growth in their UK stores, executives in British retailers are heading for the most difficult decisions of their corporate lives. Those retailers still achieving success are being underpinned by growth in their online business. Increased sales per sq ft in pure ‘bricks’ operations are becoming a retail rarity.

Across the patch, large store portfolios seem like they belong to history. And chances are that bricks’ performance will get worse under the double whammy of falling consumer confidence and a move towards more online activity.

For many UK retailers it’s now time for serious pruning of the store portfolio. But where do they start? And what are the implications of injudicious cuts? The most difficult decisions often carry the greatest risks and rationalising the store portfolio will be fraught with difficulty. The right choices will minimise the retailer’s overall turnover losses and the wrong decisions will have a much greater impact than expected.

CLICK & CLOSURE OR CLICK AND CHAOS?

Some will think the decision is easy. Open up the spreadsheet, click on data sort and close down the stores with poor sales against allocated costs. And expect that customers will transfer to their nearest store. However with multi-channel retailing and the complexities of UK consumer geography this is no time for back of the envelope calculations. Successful rationalisation will only happen by undertaking a detailed review of the UK portfolio and a thorough assessment of the place of bricks in the multi-channel equation.

FOCUSING ON THE CUSTOMER, NOT THE STORE

Store rationalisation runs the risk of focussing on the store rather than the customer. It’s important to remember that the store is merely a transaction point for customers. It can’t be assumed that the store (and by association the retailer) owns its existing customers. Particularly when retailers often know more about their online customers acquired in recent times compared to store customers who have been nameless shoppers over a number of years.

Store closures will not force changes in customers shopping patterns and so it’s vital to model the resultant loss in trade and identify stores and channels to capture displaced shoppers.

FLYING THE HIGH STREET FLAG

The internal relationship between stores and online is now much more than the operational issues over click and collect facilities. Any closure process needs to take into account the effect of closure on online trade from local shoppers.

Our consultancy work has shown a ‘brand anchor’ online benefit for many retailers in terms of existing stores and new openings. We’ve seen uplifts of up to 15% in online business in a new store’s catchment area (see Paul Langston’s earlier blog).

On the flip side, whilst store closures might not have a substantial and immediate effect on online business, scenarios need to include online decline as brand anchors are removed from the gaze of local consumers. The warning is clear – close a store and you may lose online business in the area, never mind struggling to hold on to existing bricks-based customers.

TRANSFERRING THE BUSINESS

Time was when the height of CRM in relation to store closures was the hand-written notice in the window instructing customers to go to the nearest store. With closures across the UK it will be vital to minimise the effect of closure on shopper’s spending. Reliance on staff on threat of redundancy to market the replacement stores and online channels will be asking turkeys to vote for Christmas.

It’s never too late to start collecting customer data from store customers and without that data retailers run the risk of losing their customers’ spending following closure of their local store.

Whilst closing stores may be soundly based in financial reality it’s also worth remembering the need to counter local PR issues. The fickle British consumer had abandoned branch based banking in droves but never failed to support the fight against their local closures. Marketing offers to displaced shoppers needs to be in place as soon as closures are announced. And at a national level don’t forget that loyalty can be focussed on the individual store as much as the retailer brand.

MAKING IT HAPPEN

The rationalisation process needs to be both strategically sound, tested and carefully actioned. In addition to the operational and logistical issues, our process follows the following 10 steps for a successful rationalisation process.

10 steps for rationalisation

1. Review customer shopping patterns around stores (and collect customer data if required)

2. Identify stores with highest customer overlap

3. Predict level of brick-based trading after initial rationalisation scenario

4. Identify stores still likely to fail to achieve satisfactory performance

5. Agree closure & re-size list (subject to lease issues)

6. Assess impact on online sales in closure areas

7. Identify customers (on & off-line) affected by the closures

8. Create multi-channel customer retention strategies for displaced shoppers

9. Close & re-size stores & act on retention

10. Review store performance, online sales and customer shopping patterns against predictions

Rationalisation for UK store portfolios is on the way. The only question is how you do it. Will you be the next retail disaster movie or a reputation enhanced by a carefully executed plan to focus stores on their local demographic?

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Are Stores Going Out of Fashion?

15th Jul, 2011 by Paul Langston

Paul Langston, Consulting Partner, Location Strategy

Despite some major headlines in recent months that have cited the Internet as a factor behind store consolidations, retail stores are not going out of fashion!  Yes, some retailers are struggling, but others are still very much on the growth trail, even when they have high and growing levels of online sales.

Yes, online sales can have a major impact on store viability.

We’ve seen in our work with a number of clients that this relationship can be positive, and that a store presence can improve online sales.  This is especially the case for retailers with a strong brand, clear online proposition and supporting links between their on and off-line offers.

We have seen some big-name casualties where the Internet was a major factor.  But, in my view, the impact of the Internet can be a convenient excuse, when in reality there are other pressures bearing down on retailers’ expensive store networks.

For many retailers the threat from the Internet and new technologies is no worse than the many other retail dynamics that are impacting on every store – ranging from shifting store pitch to changes in the national economy.

So that retailers are not caught out by these shifts, I believe that ongoing Network Management is essential to ensuring the long-term viability of all store networks.  This involves; regularly monitoring the unique factors at play on each store, alongside traditional metrics like profit and like-for-likes.  Only by understanding the Store Potential, Network Interaction, Store Position and level of Online Interaction acting on each individual store can retailers make truly informed decisions about their estate.

There is no shame in closing stores in a managed way in response to these shifting dynamics, and an ongoing pruning of the estate is an essential part of maintaining a healthy and vibrant store network.

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How to Instigate and Manage Data Analytics Projects

24th Mar, 2011 by Ananya Sadera

Ananya Sadera

Ananya Sadera, Head of Client Services, CACI

Instigating projects

Customer analysis and insight can help companies in a variety of ways from simply understanding who are buying their products and services, to more advanced techniques such as calculating lifetime value and share of wallet. Furthermore, this information can then be used to find and acquire prospects who look like valuable loyal customers. Simply put, insight is business critical.

However, in many companies Analysis Managers have walked into roles “where it’s purely a support function doing management information and report after report.” While the intention is to provide proactive insight, because of changing businessdemands, the reality is that most analytic teams end up being more of a reactive/supportive function.

Richard Tomlinson

Richard Tomlinson, Head of Analysis, CACI

However, when analysis teams action repetitive requests, they are unable to spend time and provide the little nuggets that can be truly ground breaking, the little details that tell them not only which customers are leaving but why, when and what are all the different variables that lead to this event. Nuggets that might provide direction to the business by identifying new markets or potential threats.

To avoid having a team fall into this cycle, one recommendation is to structure the analysis team into two functions – one responsible for identifying and reporting on the key customer questions regularly asked by marketing teams, and a separate team responsible for proactively driving additional insight. Separating the two provides the bandwith and time for the insight team to instigate true insight.

Managing data analytics projects

Data analysis projects come with their challenges and the following tips provide some ways of getting around these:

1)     Data availability

We have seen a number projects that have not come to fruition because data availability is only discussed after project sign off. Only then does it become apparent that the customer or market data required is not readily available from core systems and so timescales will have to be totally revised. Always check to see if the data sets that are to be the building blocks for your project are available. For example, in-bound call centre data is usually key for retention modelling and in most organisations is not linked to the marketing database.

2)     Stakeholder management – know your audience

If the key stakeholders are from a business background, make sure the results are based on business relevent questions and not too technical. They might not be interested in code! Similarly if it’s a technical audience that has ultimate sign off make sure anything they want to know, such as the variables used and model strengths, are addressed. For example, for a marketing audience, presenting a profile of the top decile of a propensity model will be received better than a gini coefficient!

3)     Regular feedback meetings

A common occurrence on these projects are instances where there is a huge gap in what companies percieve as their customer base to what it actually is. Regular meetings during a segmentation project and the sharing of findings as you go along ensures there are no surprises at the end of a project and concerns are addressed as you proceed. For example, a sophisticated clustering algorithm may identify a niche group of high value, older and low affluent customers. Can the business work with a such a group? Is it of sufficient size to tailor propostions to?

4)     Rescoring and rebuilding 

A short time after a segmentation or modeling exercise, comes the question of refreshes and updates. Be clear at the outset on terminology:

Rescoring or Refreshing: Using the current algorithm to update a customers score or segment.

Updating or Rebuilding: Revisiting the original project and refining or totally re-creating the algorithms.

Agree at the outset on the timescales and on how often these will takeplace. It may be relevant to re-score in real-time in some high customer activity organisations such as the telecoms sector, although quarterly re-scoring is the norm.

The typical lifetime (before update or rebuild) of a model or segmenation is 2-3 years, but it is prudent to check on a quarterly basis that the solution is still fit for purpose and the profiles and performance of the algorithms are still in line with what was seen when they were first built.

Analysis and insight are like a puzzle, putting the different pieces together to complete a picture. The key is having a structure in place that allows this to be a focus and managing information so when the final picture is revealed there are no surprises!

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Monitoring Social Media – Analytics and Web 2.0 Data

17th Mar, 2011 by Chris Geddes

SOCIAL MEDIA IS EVERYWHERE

Social Media has yet to have a definition truly nailed down. Wikipedia, an apt source for this information, states that “Social Media are media for social interaction, using highly accessible and scalable communication techniques”… which is interesting. It means that ANY medium through which a two-way conversation can take place counts as a Social Medium which, in turn, means that the pub counts.

This is an interesting (and I believe accurate) perspective as the logical conclusion we can arrive at is that not much has changed between pre and post Social Media: We are still, effectively, talking about “word of mouth” except, this time, it is on steroids. Whereas in the past a conversation in a pub might influence a handful of people, it is now possible to influence tens of millions of people. Herein lies the power of Web 2.0 Social Media: The voice of the customer is now broadcast, linked and amplified to a far greater extent than ever before.

Its not just 140 character “tweets” that the comments are made through. Facebook updates (and updates on other social networks), YouTube videos and Forum comments also add to the noisy conversations that are happening 24/7.

When I ask clients whether or not they use Social Media, they often respond along the lines of “Do I look like I use Social Media?” but upon further probing, most do indeed use Social Media. Most people think that Social Media are the same thing as Social Networks… not so. Most of the clients accept that they use Social Media when I point out that Amazon, Ebay and Google all have social elements and if they have used any of the reviews (or other User Generated Content), then they are, indeed, users.

The reason I have spent so long in explaining what Social Media really are - is so that it is understood just how much UGC there is “out there”. No single corporate entity can afford to store all of the Social data that is produced by users -there is just too much – so how do companies make it manageable and leverage the reams of data?

SOCIAL MEDIA MONITORING

Social Media Monitoring tools have been around for some years now, but are only just starting to really get to grips with the volume and diversity of content. Essentially, they all work by trawling the internet for specific triggers and then pulling back the information, rather than storing it all in an enormous database and then running queries. The main difference to the user of one of these tools is that it is easier to start a search and allow it to run into the future than it is to try to go “back in time” through searching stored information, unless the information is stored elsewhere. Sites such as Twitter, however, don’t keep the “tweets” for long, though, so running a search to measure the effectiveness of a new product launch, for example, has to be done right first time… there are no “re-dos”.

Its not just keywords, though, that the budding Social Media monitoring employee should think about. Software is now advanced enough as to understand sentiment to a useful degree of accuracy, and even sarcasm… which is soooooo easy for us humans to pick up, but much harder for machines. The mechanism for flagging remarks as sarcastic is long, though, and complicated and a subject for another blog post sometime, but the point is that these tools are well established and can whittle the billions of comments made every day down to those that are relevant to you or your brand at which point, I would suggest, a human being deals with them.

If you decide not to use any of these tools, you could watch Twitter, for example, 24 hours a day, but what about the other 500+ major social media channels? Its going to be expensive to hire the manpower necessary.

Fig. 1: Social Media Monitoring Tool classes

Genre of Social Media Monitoring Tool                What it does                                       
Keyword monitoring Monitors the (public) internet for keywords or phrases
Buzz measuring Monitors the volume of comments concerning a topic (collection of keywords/phrases) or keyword
Sentiment monitoring Measures the feeling associated to a topic or keyword
Association monitoring Monitors a keyword for frequent associations with other keywords and their associated topics
Influence monitoring Measures influence of online or offline individuals in the online space

So, what vendors are the best ones for you? That’s a tricky question. When I last counted how many Social Media monitoring tools there were “out there”, I got to 168, each of which has its own strengths and weaknesses to evaluate, which is not the purpose of this blog post. The purpose is to address how best to use Social Media monitoring tools to analyse Web 2.0 data (or so it says in the title).


USING SOCIAL MEDIA MONITORING TOOLS TO ANALYSE WEB 2.0 DATA

There are two ways that these tools can be used to enhance a company’s insight on customers, both current and prospective.

1) Monitor the public activity of known individuals and this, in most cases, requires some kind of opt-in from them and is thus hard to achieve (but immensely valuable).

2) Address customers and prospective customers as one entity and see how people are reacting, in real-time, to various stimuli en mass.

This approach could, for example, give a good indicator as to the impact a new advertising campaign is having on discussion volume and sentiment and provide feedback as to how to improve it … or whether to remove it.  If taken to the extreme, this data can be mapped and segmented into very precise, small segments which, with the aid of a representative sample of the population, be mapped back to your own customer data… giving new levels of customer understanding to the data analysts. Let me give an example: Customer data indicates that I am a male, I am 27 years old and I earn £200k a year (I wish!). It also shows that I live in west London and drive a motorbike. Finally, it states that I spend £100 a month with your company. With the online profiling just mentioned, it is possible to see what online behaviours others that share these characteristics have, such as hobbies, holiday destinations, favourite cartoon, least liked food takeaway type, political leanings and anything else you might want to know.

It really is that powerful if handled right.

Why would you want that kind of modelled information on a customer?

Knowledge is power - power to stop bombarding customers with irrelevant marketing (and thus power to market more effectively), power to design products and services around what your customers are likely to want, not what you think they will want, power to engage with customers about things they care about, not what you think they care about but overall, it’s the power to listen and let your customers know that you are listening.

Since customers that feel a company cares about their opinion sell around 50% more effectively than companies that don’t, I think the argument for Social Media Monitoring pretty much sells itself, don’t you?

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