Tag Archives: single view of retail customer
In my marketing classes, I like to share on the works of Michael Porter’s Competitive Strategy. This includes discussing his three generic business strategies. We discuss, for example, the difference between an “efficiency strategy” (aka Walmart) and an “effectiveness strategy” (aka Target or even better, a high end service oriented retailer). I always make sure that students include in their thinking on differentiation the impact of customer service.
One of these high end service oriented retailers is using technology to increase its customer intimacy as well as holistic customer knowledge. Driving this for them involves understanding when customers use their full price and off price customer purchase channels. I was so fascinated about their question that I decided to ask the font of all wisdom, my wife. She said that her choice of channel is based on my current salary or her projected length of use of an item. So if she is buying a jacket that she wants to use for years, she will go to the full price channel but for a dress or pair of shoes for one time use like a Wedding, she will go to the lower priced channel. Clearly, there is more than one answer to these questions. This retailer wants to understand the answers by customer segments.
To create an understanding of each customer segment, this retailer wants to create a “high fidelity” view of data coming from customers, markets, and transactional interactions. This means that that they need two new business capabilities. First is a single integrated view of their customers across channels and the ability to see the cause and effect of customer channel selection decisions. Do customers spend more time at the full price channel option when, for example, sale offerings are going on?
To solve these problems, the retailer has implemented two technology approaches, master data management to bring together its disparate views of customer and big data for quick hypothesis testing of customer data from structured and unstructured sources. With Master Data, they get a single view of customer across differing IT systems. For separate customer specific analysis they have created operational and analytic views on top of the MDM system. And while they have an enterprise data warehouse and multiple analytical data marts, they have also created a HADOOP cluster to test hypothesis about the cross channel customer segments. They are using the single view of customer regardless of channels and transaction history to understand when customers use which channel and as well what marketing or other campaigns pulled the customer in. With this, they are creating inferred attributes for customer market segments.
Clearly, the smarter the retailer gets, the greater the differentiation the retailer services can be to customers. At the same time, the data let’s the retailer optimize marketing between channels. This is using data to create service differentiation.
Retailers have long recognized the value of a single customer view, but the emergence of multichannel research and shopping has made achieving that ideal more difficult. Today’s consumers hopscotch across online, in-store, call center, social media, mobile, and other channels—how can retailers keep up?
If you have a single view of your retail customer, you can assess channel buying preferences and tailor marketing accordingly. You can deliver the personalized and consistent experience that discriminating consumers expect across all touchpoints. And you can take advantage of the unique cross-sell and up-sell opportunities that multichannel environments offer.
For instance, if Jane buys a $2,000 leather couch in a store and you can match her information to the email address she registered three months earlier at your Web site, you’re in a great position to pitch matching pillows with a personalized email.
But, as outlined in a new Informatica executive brief, siloed data systems for point of sale (POS), e-commerce, call centers, and more make it difficult for retailers to achieve a single customer view. The brief includes survey results from a leading research organization, including the following statistics:
- 92 percent of retailers don’t integrate customer data from all channels
- 68 percent of companies cite improving customer data integration as a top priority for 2010
- Less than 25 percent of retailers extend personalized loyalty programs across all channels