A Shopaholic’s Guide to Analytics


If you know me, you know two undeniable things (other than my love for froyo): I consider shopping a sport and I am an Analytics geek. Being an Analytics geek means that I see potential for using data everywhere, and never more than when it’s my data as a customer. And through sheer perseverance – I think of it as contributing to the economy (I’m not an economist) – there’s a lot of it sitting in data stores around the world.

Privacy aside, as far as I, the customer, am concerned, the data is there so that I can have a better experience, and so that my retailers and service providers can make (just) enough money to keep improving my experience.

As a customer, what do I want?shopper

  1. The right product – don’t you hate not being able to find the thing you have psychologically and financially prepared yourself to buy?
  2. Good service – I want to be a (very) repeat customer so give me a reason!
  3. A feeling that I got a good deal – at least in my head…
  4. Convenience – with work, friends and family, I am all about efficiency.

Turning the (credit) card over, for a retailer or service provider what do these four points mean?

The right product – do we know how demand for our products will change?

Do we know our peaks and troughs in demand to make sure that shelves are never bare without the right products and that our storage space is not wasted on too much excess stock? There are few monopolies now in retail and so as a customer it’s much easier for me to spend my money somewhere else in town or somewhere else in the world online. And if I have to go out of my way to find a particular product, I am (most) likely to buy other things while there.

bottlesIs demand consistent like cooking chocolate that spikes 6-8 weeks before Christmas, or ice cream that is driven by changes in the weather? Or is it irregular like a fashion item that comes in and out of popularity based on advertising investment, celebrity endorsement or what happens on the Paris catwalks?

What are our product demand trends and what are the things that impact them?

Good service – what can we do to attract our customers back?

If you want loyalty, the shopping experience needs to be emotional. Other than pleasant and helpful staff that appear magically at the exact time they’re needed, what services suit the personality of our products and expectations of our target customers? It may seem counter-intuitive but there is a café in my city that is known for its less than nice staff to match its moniker – but it’s always packed, probably because of its wide selection of cakes, and inner city location near a university.

happyWhat are our customers saying in surveys, verbally and on social media? Are they checking in with positive or negative comments? Do they like our décor or do they want more cake options? Once we know who our target audience is and how they think, we need to ask where are our target areas to setup shop and what products should we stock up on? Is there a group of customers that are high value and need more attention?

How do our customers actually feel about us and what can we do to keep improving?

A feeling that I got a good deal – how often do we need to run promotions?

Let’s not beat about the bush, when I see “SALE” I have an instinctive need to enter into the uncomfortably crowded store and generally feel obliged to make a purchase. But I, and my bank, wouldn’t necessarily classify me as a bargain shopper. So what is the right amount I should be promoted to – both to retain my loyalty as a customer but stay profitable as a retailer?

offerWhat is our point of diminishing returns for promotions – is “more” better, or is “more” just more? Does buying a hot chocolate mix cannibalise on instant coffee? Could promoting a cheaper red wine still lead to the purchase of a more expensive red wine with the cheaper wine? Is “30% off” more attractive than “Buy 2 get 1 free”? To really know, these variations need to be compared and tested. For a small number of products, knowing our customers and products could be enough but where there are unknowns, we need analytics to help provide those answers.

Do we know the price tolerance of our target customers for our products and the maximum quantity cap per customer?

Convenience – are we using the right channels for our customer?

Some may say that convenience is just another word for lazy, but with so many competing activities, convenience is a necessity. Like when I discovered online shopping (sighs). For me, it’s just another channel for my sport, though a channel that sometimes disappoints because I am a tactile shopper – sitting behind a computer is just not as much fun. But it’s so convenient (and dangerous).

mobileWhat are our customers expecting – what makes sense for our products, environment or culture? Which of our products make sense to have in-store, online, sold through consignment or some combination? Do we need apps for online purchases? Should these apps have embedded payment methods? Should we include free shipping (yes!) or same-day delivery? Does everybody deserve this service or should it be exclusive?

How can we get our product closer to our customers in the most cost effective way?

So many questions and so little time, where do we start?

It's not immediately with the data, though there is a lot of this and analysing it is important.

  1. First step is to ask: what is our ultimate goal – is it customer satisfaction, profit, exclusivity, humaneness…?
  2. Ask questions from our customer's perspective - use our personal experiences if we are the target market - and map it to our goal. We need smart people - domain, objective and subjective experience and systems knowledge - to ask these questions. There are no wrong questions but as we learn new things from the data we didn’t previously know, we will find better questions to ask.
  3. Anything we don’t know straight away – demand shape, ideal customers, regional profiles, customer sentiment, price sensitivity, optimal contact points, economic breakdown – we can almost definitely find out through the data available internally (price, promotions, supplier, POS transactions, call centre) or externally (competitive, industry and economic trends, social media, disruptive strategies).
  4. Most importantly, be open to the results – every surprise is a free gift from our data.

Stay tuned to the next instalment for more on how to get the right answers to our questions. If shopping was a sport (pretty sure it is), it would be a marathon rather than a sprint, just as analytics is in retail – we must start somewhere, some is always better than none, and with a clear goal and the right support, we can build on smaller precious victories and become a champion.

For avid shoppers, retailers and service providers, start getting competitive offers at the SAS Retail Analytics store of information. Eager to learn more and get hands on with a retail-specific scenarios? Visit the SAS Visual Analytics Try-Before-You-Buy website. Scenarios include Customer Analysis and Promotion Effectiveness.


About Author

Business Solutions Manager

Annelies believes that there is potential for Analytics everywhere. She works as an evangelist, enabler and execution strategist to empower individuals and organizations with good Analytics practices. Annelies is the Advanced Analytics technology lead at SAS Australia and New Zealand responsible for product management and enablement. During her career, Annelies has held various positions supporting the customer lifecycle from strategy and requirements to implementation and adoption. This experience gives her a practical view of the end-to-end process of data analysis across government and industry, including engagements in several customer analytics, demand forecasting, text analysis and allocations optimization projects. Annelies is the current co-chair of the NSW Chapter of the Institute of Analytics Professionals of Australia, the largest analytics community in Australia. She has a research Masters in Mathematical Statistics and guest lectures at several tertiary institutes in Australia.

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