The still untapped potential of effective Customer Data & Analytics


The still untapped potential of effective Customer Data & Analytics

A few recent headlines:

“GSK (Glaxo) announce partnership with McLaren Formula 1 motor racing to access their expertise in big data analytics”

“ unlocks the value of real-time analytics”

“IBM now have a team of 15,000 worldwide focussed on Data & Analytics”

“American Express forges new customer relationships through deep analysis and research”

“Uber, Amazon, Netflix have been pioneers in data science, machine learning and predictive analytics, they are now being joined by a host of others”

“Alexander Stojanovic, VP at eBay, describes how analytics is at the heart of their key business decision-making”

“Beth Butterwick, CEO at Karen Millen, has commented: “if we truly understand the customer data, understand the journey from beginning to end, then we have the strategic horsepower to influence the entire organisation”


Cutomer Centric


Few doubt the value of analysis to drive better decision-making. In these days where there is a “deluge of available data” there is a growing imperative to find ways to capture, interrogate and find the key insights that can drive competitive advantage.

However, a recent study from the Aberdeen Group showed that a surprising 78%! of company executives felt that their organisations “struggled to make effective use of customer data”. At the same time, those who were able to master customer analysis and insight showed remarkable results. They could point to increases in:

  • net new customer revenues
  • revenues from customer referrals
  • cross-sell and upsell gains
  • plus improvements in annual % customer service costs.


Customer Analytics Users Maximise Their Revenue


The winners, the “customer data masters”, are companies like Starbucks, Amazon, Wells Fargo, Sainsbury’s, Citibank, Adidas. And success is not only the preserve of large multi-nationals; smaller local companies can also take advantage without spending $Ms to do so. Here’s a few case study examples:


Lia Vakoutis, Senior Director at Adidas, has described how they have mined social media data to drive new product sales:

“We used to prepare promotions months in advance. Because of the cost and time invested we used to just roll them out hoping they’d work ok. But if they didn’t it was too late to do much to change. So we made a decision to move from “reactive marketing” to “predictive marketing”.

“To achieve this shift in Marketing and promotions planning, we now use a variety of tools to monitor social media sentiment including SalesForce Radian 6 (social media /Marcomms monitoring in real time), Sysomos (provider of infographics and reports on competitive social media performance), Crimson Hexagon (manages /analyses big data). All these can work together to produce the most detailed picture of what’s going on in our social media world”

Adidas focus on 4 key social media fora: Twitter, YouTube, Facebook and Instagram.

They are analysing for example some 1200 soccer specific message boards, blogs, new sites. A recent campaign count showed they had analysed over 4 million pieces of information across 17 markets in multiple languages. Because the analysis and insights are coming through in real time, Adidas can shift promotions, feature the sports stars who are getting more traction and response, change promotional material, add or change copy, influence conversations and also react immediately to competitor activity. “It’s just a brilliant way to test what works and what does not, and be able to react instantaneously. In one recent campaign we were able to test and monitor 300 different concepts in one 48 hour period”.

Amazon are so often cited these days as best practice, but when I interviewed them, they spoke about the following:

“Of all the things we do today, we believe it’s our real time customer analytics that make the difference.

We have a team monitoring customer activity by the second and we can see immediately what’s working, what’s not, we can identify price change opportunities, page lay-out changes, product-bundling and we can check this across all users and our whole customer base”.

“What really makes this data monitoring work is that we use it and make the changes in real time too. How do we do that? We have a “virtual circle” of Analytics, UX/Conversion and Web Dev. That is made up of three core groups of people who work very actively together. They are co-located, they report to one person, they are the key commercial grouping”.




That sort of real-time analytical plus change capability is rare. Some companies with similar fast-moving /fashion /consumer-driven businesses do try to organise in this way. For example retailers John Lewis and Next. But what even these successful organisations lack is that corresponding real-time change capability. They still impose too many checks and controls to make that work easily.

One more case study comparing Starbucks with Pret a Manger.


Starbucks introduced its customer loyalty scheme some 10 yrs ago. It is recognised as being the most successful loyalty program in the USA. The My Starbucks rewards program started as a simple payment card before it gradually evolved into the successful rewards scheme it is today (“one sip gets you gold status”).

Howard Schultz, when CEO and then Chairman, updated shareholders at an AGM: “More than half of My Starbucks’s 15.3 million members are high-spending gold members, in addition more than 23 million use the mobile-payments app and in one quarter alone more than $2bn was loaded by members onto their cards”

“We can do all this and make it easy for members because we have invested in building our customer database and capability. It means that we can see what our members are doing and critically these days we can personalise and tailor all our customer communications so each member can feel some personal connection with us”.

Starbucks uses Oracle Siebel customer relationship management (CRM) software as its loyalty system, which is tied to the Oracle ERP platform. This delivers a combination of transactional, analytical and engagement features to manage all the sources of customer data, no matter if it’s in-store or on mobile. That ties into their cloud-based Oracle “Exadata” data warehouse for scale.

Starbucks has massive amounts of data that needs continuous cleansing and analysis and with c. 4 billion+ cups of coffee sold each year that is a lot of data! “…and we still have not been able to get all the insights out that are possible”.

Pret a Manger

Pret a Manger on the other hand has taken a very different approach to customer loyalty. Instead of building extensive customer databases, their approach is to leave loyalty up to each employee’s discretion. “We looked at loyalty cards but did not want to spend all that money building up some large scale Clubcard-style analysis”. Instead, the Pret approach is described as “freestyle and fun” empowering employees to give away eg free coffees.

On the one hand, Pret has received praise for its innovative approach and it certainly ties into the company’s culture. But critics point out that such freebies are arbitrary and whimsical and easy for genuine loyal customers to be ignored and overlooked. Also it’s pointed-out that the lack of customer data insight might surely disadvantage Pret in the long term as more data-driven schemes work to develop that ever closer customer connection and relationship?

With these sort of case studies showing what possible and what can be achieved, why is that 78% of executives in the Aberdeen Group research are frustrated with their own company’s lack of progress in this area?

A recent Harvard Business Review study showed that 53% of execs surveyed by them felt that: “getting the customer experience right” was an important strategic priority (one wonders about the other 47% who did not agree with that statement!). But there was a broad consensus about the key challenges to be overcome:

(i) Proving the RoI: companies find that while there can be many customer improvement initiatives it can be difficult to clearly attribute and show which initiative is delivering what RoI and this makes further investment cases hard to validate. So half of the companies in the HBR survey said that: “it’s still a struggle to fund customer experience programs”

(ii) “Deluge of data”: “there’s now so much potential data available but what are we going to do with it all?”

(iii) Multi-channel complexity: “we are looking at data from web, store, email, social media, tele-sales, call centre, field sales, Mobile, customer query handling, past purchase records…even assuming we capture all this data accurately, which we don’t, then how do we get to a unified view?”

(iv) Data integration /standardisation: Only 18% of companies in the HBR survey felt that they had an integrated data capture system. “We have different departments operating in silos with their own databases and drawing their own conclusions. Efforts to tie the data together meet 100 reasons why not”.

(v) Lack of key skills: Is there a Chief Data Officer? If there is, how much of that person’s time is deep in data science, or do they also work to drive the insights into the Marketing and customer decision-making process? Is each of the areas in the Customer value chain effectively being staffed and led? Is that whole chain of value being brought together, coordinated and championed by one senior Data/Analytics /Insight Officer?

(vi) No unifying Dashboard /metrics /KPi: Both in the HBR and the previously mentioned Aberdeen Group surveys, a key reason cited for lack of progress was the absence of a clear set of metrics and KPi. There was no agreed measures of what was successful customer experience, there was no comparison of how well the company was doing vs. competitors in this area or vs. more widely relevant benchmarks, no way of identifying and agreeing what was working and what not, no insight to show what the improvement gaps might be, no understanding of what the full potential could be if customer engagement was truly optimised.

(vii) No use of NPS: NPS or Net Promoter Score is fast becoming the global standard for measuring how well a company is delivering on customer service. It’s a system pioneered by Bain Consulting and Satmetrix. Its power lies in the monitoring and measuring the NPS trend and benchmarking vs competition.

Those who embrace NPS see it as the key catalyst and start of their Customer Analytics journey. “It’s an objective market study, it shows how we’re doing and it compares our performance, it has galvanised us into defining what other metrics we needed and how to go about getting that data and insight together”.



Let’s look at two company cases studies where they seem to have effectively managed their way through these significant challenges:


Countax are a great independent manufacturing benchmark, They produce lawnmowers, UK-based, distributing worldwide, just 120 staff. Darren Spencer, one of the senior Directors, commented: “Our business had long suffered with insufficient or difficult to access data across all aspects of our operation and especially in better understanding our distributor and end-user customer base. Quick access to information we trusted was just not possible. We had the data, we just couldn’t use it or it was very painful to get it!”

Countax hired a Business Intelligence software firm called Matillion who set about implementing a SaaS data warehouse solution which would integrate with their ERP as well as with other in-house developed bespoke systems. The areas of BI and data integration covered Sales, Inventory, Supply Chain, Customer Data and customer purchase /contact history. Data inputs and definitions were defined, the key dashboard metrics were agreed and a major effort took place to unify and standardise so there would be a single and common view of all the data insights.

Now Countax has a self-service BI environment which is designed at various levels of detail so that even the non-data literate can access, interpret and digest. “The reporting ability that comes from this business intelligence has greatly helped. We now rely on these analyses to guide the strategic direction; we didn’t have this level of visibility before. And because we have a common dashboard it makes our management meetings much quicker and easier, there’s no debate about the data, it’s now simply about what actions to take…wish we had done this years ago!”


Sainsbury’s CEO Mike Coupe sees customer data analytics as the key to the company’s future success: “We are aiming for a future where we know every single customer on an intimate basis...we want to be able to predict what our customers will need, when they’ll need and how best to deliver that to them”.

Sainsbury’s has been on a long journey collecting and building “a vault of customer data”. But in its early days that information was accessible to only a few analysts and coders. “ We weren’t using the information to its full capacity, it wasn’t easily accessible to Buying, Merchandising and Marketing and so we were short of the customer insights needed to break new ground”,

Sainsbury’s teamed up with Aimia (and subsequently acquired them!). Aimia are customer analytics /loyalty specialists, and together developed a 6-point strategy and change programme:

(i) Identify the key metrics: This was a critical step: what are the key measures of effective customer engagement and how be sure to measure those things that can truly drive sales. Sainsbury’s has developed a wide list of these KPi which include basics such as trends in average spend, basket size, frequency of purchase, customer lifetime value etc to derive a “loyalty index” and allies with that with more emotional /sentiment scores derived from research, online surveys, social media and NPS scores. All this done not just at a store level but where possible at an individual customer level.

(ii) Train staff, continuously, in Customer Service

(iii) Build a dedicated team: now c. 120+ people responsible for customer data management, analysis, reporting and insight. Reports are tailored for each department so eg Buying will get its own set of analyses and insights as well as seeing the bigger picture.

(iv) Monitor use of the data insights. A key task of all senior managers is to ensure the data insights are followed through and actioned.

(v) Personalisation: Develop customer marketing and promotion campaigns and initiatives that allow individualised, personalised customer comms.

(vi) Supplier investment: Sainsbury’s has worked with its supplier base to give them access to this customer data and insights. The aim is to help suppliers identify what sells best, innovate and develop products that customers want, see which promotions work best and generally enable them to maximise their own business activities.

In a recent statement, CEO Mike Coupe has re-emphasised the need to continue to invest in this area: “It’s on-going to address the changing and multi-channel needs of customers. So we want to still improve the in-store customer experience with further investment in staff training and a new automated system to track availability. We are also committing to further systems infrastructure to create a single view of customers, leading to increasingly effective interactions”



Whether it’s Sainsbury’s, Starbucks, Netflix, Countax or John Lewis, whether B2C or B2B, in today’s highly competitive world, companies are of course having to work harder to grow and be successful. Few would argue that “developing an intimate understanding of our customer” is not a major imperative and need. The challenge is to establish that company-wide commitment to getting those data analyses and insights together in a unified form that can drive decision-making and enhanced customer engagement. Will future Aberdeen Group surveys continue to show 78% of companies struggling to build an effective customer analytics platform?


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© Michael de Kare-Silver 2024

Michael runs this specialist and international recruiting /headhunting practice Digital Prospects, helping companies recruit key talent where Digital Tech and /or Data skills and savvy are important.

Michael used to be MD at and of, he is ex McKinsey strategy consulting and Procter & Gamble marketing, Michael provides a personal and dedicated advisory and recruitment service that delivers results and is built on treating people with kindness and respect.