More effective operational marketing for retailers

Combining off-line and on-line customer data improves customer understanding

Retailers today have the opportunity to vastly extend their customer knowledge. Today’s technology enables them to gather commercially interesting information during their off-line and on-line purchases. A robust analytical system such as SAS, can integrate both off-line and on-line customer data to the retailer’s benefit. It will enable him to increase the effectiveness of its marketing efforts, improve purchase predictions, and optimize customer experience in every circumstance.

 

Technology opens opportunities to increase customer understanding and improve operational marketing efforts.
Professor Gino Van Ossel

Professor Gino Van Ossel
Marketing Competence Center at the Vlerick Leuven Gent Management School

Mieke De Ketelaere

Mieke De Ketelaere
Business Development Manager Customer Intelligence at SAS

Multichannel data enables retailers to personalize and improve their operational marketing initiatives.

Beyond basic customer segmentation

For the most part, retailers still only use customer cards for very basic customer segmentation. In most cases, the cards merely register the dispensed amount and the time of purchase. This enables retailers to identify customers that generate the largest turnover on a yearly basis.

In order to turn ‘good’ customers into ‘better’ or even ‘best’ customers, retailers rely on operational marketing initiatives such as discount vouchers. But, which products are the customers really interested in? ‘To find out, retailers increasingly gather information from their customers,’ explains Professor Gino Van Ossel of the Marketing Competence Center at the Vlerick Leuven Gent Management School. ‘They inquire about the customer’s marital status, pets, kids, etc. as part of a customer card registration process. This enables retailers to learn which customers may be potentially interested in, for instance, a pet food coupon.

Towards more strategic segmentation

Such single variable segmentation has long been the standard. And in most cases it still is. Professor Van Ossel: ‘Previously, computers could only process a limited amount of data. This is no longer the case. Unfortunately, segmentation analysis didn’t evolve accordingly, due in part to the difficulty of finding the appropriate variables and developing proper hypotheses.

A few years ago, a large UK-based supermarket chain took up the challenge and achieved significant success. They developed 25 criteria to score each of their products. These included such characteristics as ‘cheap’, ‘fresh’, ‘for kids’, etc. They linked this so-called product DNA to the product’s logistical article code. ‘It is a time-consuming effort, but it opens a whole new world of opportunities,’ declares Professor Van Ossel. ‘Where the variables are relevant, a robust tool such as SAS is able to segment customers based on a multitude of variables reflecting their purchasing behavior. This is valuable input for more effective operational marketing.

Taking into account on-line customer behavior

Nowadays the website is an increasingly important channel for retail. Ever more people are buying on-line. Or they are looking up information on certain products before heading down to the local store for their off-line purchase. In other words, the customers’ on-line activities become equally important to understand overall purchasing behavior.

Today’s technology enables retailers to gather information about a customer’s on-line behavior. ‘It is perfectly possible to register which brochure a certain customer has downloaded. Or to find out which products a customer is checking on the website,’ illustrates Mieke De Ketelaere, Business Development Manager Customer Intelligence at SAS. ‘It does not even need to be a customer. On-line analyses also make it possible to gather valuable information on interesting leads. Integrating all of these on-line data with the off-line information connected to the customer card will greatly increase insight in people’s buying behavior.

Personalizing operational marketing for more effect

As retailers use more variables to profile customers, they vastly increase their ability to influence customer purchasing behavior. ‘They can use this increased customer intelligence to optimize their marketing efforts,’ states Professor Van Ossel. ‘Previously, retailers sent an identical folder with coupons to all of their customers in the hope that some would be interested. Thanks to multivariate segmentation, they can now put together a personalized folder for micro customer segments with coupons the retailers know will interest these specific customers. Using digital printing, this customization can even be accomplished at low cost.’ The organization also uses the system to perform Economic Value Added(EVA®) analyses of its services. “Thanks to SAS, we can now run EVA® analyses for each of our services and calculate whether it generates a return that exceeds the cost of capital, taking into account the original investment.

Real-time interaction with customers offline and on-line

The better retailers know their customers, the better they can meet their needs. Even at times that the customer’s favorite item is not in stock. At that moment the multichannel data can help retailers to advise the appropriate action on the spot. ‘It could, for instance, be worth it to offer an A-list shopper a more expensive item at a 15 % discount,’ explains De Ketelaere. ‘The same interaction is possible on-line, ensuring a specific customer the same service level on-line as well as off-line. This way, the customer enjoys an optimal purchasing experience in any circumstance.

More accurate purchase predictions

Taking into account more customer data also improves prediction accuracy. It, for instance, enables retailers to more accurately predict a customer’s next purchase. Professor Van Ossel illustrates with an example: ‘A customer buys some plaster board at his local do-it-yourself store. If that person has bought plaster board on an occasional basis during the last six months, it most likely concerns a professional builder or construction worker. However, if that person has been a customer for a long time but never bought plaster board before, chances are that he is renovating his house. That information leads to the question: when will he start painting or wallpapering the new walls? Knowing that this is a high probability presents the retailer with the opportunity to offer discount vouchers for paint, wallpaper, and other related products.

New opportunities to valorize customer information

Besides personalization opportunities, multivariate segmentation could also open up a new market. In-depth knowledge about the customer is extremely useful for product developers. ‘A company that releases a new type of razor blade will want to know how the introduction is paying off. Who bought the product? And, more importantly, who returned to buy the product a second time? Previously, only market research agencies were able to investigate this via their consumer household panels. Retailers now have the means to investigate this as well. What’s more, if it concerns a large supermarket chain, they can check it among millions of their customers. This certainly is a valuable advantage over traditional research agencies,’ concludes Professor Van Ossel.

Vlerick Business School

Challenge

Making the most of off-line and on-line customer data to optimize operational marketing and customer experience

Solution

SAS® Customer Intelligence Platform solutions

Benefits

  • Increased marketing effectiveness: gathering more customer data off-line as well as on-line enables more personalized communication. This greatly increases the effectiveness of operational marketing initiatives.
  • Improved predictability: by adding more variables to the analysis, the retailer is able to predict customer behavior much more accurately.
  • Enhanced customer experience: in-depth insight into multichannel customer behavior enables retailers to further customize their product offering to optimize customer experience at all time.
The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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