Retaining old customers and acquiring new ones have always been focus points for retailers. New technologies, new product choices and fierce competition in the retail space – all these add to the complexity in deciphering consumer behavior. In such a scenario, how do retailers find answers to the what, why, when and how about their customers? Customer data management is the Holy Grail for understanding consumer behavior, and if done right, can help retailers not only understand historical consumption patterns of their consumers but also predict their future buying behavior.
Today the consumer leaves behind a trail of data at almost every touch point. Social media, POP, promotional e-mailers, credit cards and not to forget customer loyalty cards- these have become major sources of consumer data for retailers to mine. However, the sheer volume of this raw data is likely to be overwhelming for a retailer if he fails to connect the data and transform it into meaningful information.
The correct analysis of this information can help in channelizing business and marketing decisions, so shouldn’t managing customer data should be top priority for a retailer? Why is customer data management an outsourced activity when it brings much more value to retailers if performed in-house?
Outsourcing customer data management- what are the risks involved?
Customer data management is routinely seen as a non-core function by retailers. More often than not, retailers take the decision to outsource this crucial business process on various grounds – either the organization lacks the technical expertise in data design and programming, or it wants to focus more on key functional areas. While retailers are knowledgeable about their overall business, there is often a misconception that they require a lot of technological understanding of the nitty-gritties of a technical process. Outsourcing data management is thus seen as a viable trade-off. But is it really?
Outsourcing – and offshore outsourcing in particular – continues to be a key part of many companies’ supply and cost management strategy. Many retailers believe that it is more expensive to analyze data in-house than it is to outsource the activity, but they don’t take into consideration the significant risks that arise when they send out data. If not properly managed, retailers may negatively affect their operations and customers.
Got a query? Wait in line: One such area that often suffers in the process of which retailers getting their customer data management activity outsourced is the response time. The customer data management vendor has several clients, out of which your retail organization is just one. If you have a query, it might just get stuck in the whole list of queries the vendor receives each day and this causes a delay in the response time.
Here’s how effective that promotion you ran last month was: To add to it, the analysis of this data is never real-time. Let us say as a retailer, you’re running a campaign for which you actually require real-time analysis to further fine tune the campaign while it’s still live. If you outsource your customer data management and analysis, this is technically not possible.
Data for your vendor’s eyes only – or so you hope: Data security is another critical issue. For you as retailer, your customer data is highly confidential and by giving it to a third-party, you face the potential risk of losing it to your competitor who may also be using the same vendor. It’s definitely a catch-22 situation: if you cannot protect your data, you put your business at risk and if you constrain the use of your data by your vendor too much, then the customer analysis remains incomplete.
Here’s the big picture – byte by byte: Most of this outsourced customer data management does not provide retailers with a holistic picture. Outsourced data management typically deals with the analysis of specific data sets, for example: basket analysis of a customer or demographic segmentation and likewise. In the end what one gets are disjointed pieces of information, which doesn’t help retailers gain complete insight into customer preferences and behavior.
What retailers could do if they performed the activity in-house?
Target’s ability to identify pregnant shoppers and literally target them with customized offers is now legendary. While the retailer has been collecting data about its shoppers for years, members of Target’s Guest Marketing Analytics department are the in-house data wunder kids who have got customer pattern identification down to a science. Because the retailer is in possession of the data attached to say Jane Doe’s Guest ID number; the retailer knows how to trigger Jane’s habits. They know that if she receives a coupon via e-mail, it will most likely cue her to buy online. They know that if she receives an ad in the mail on Friday, she frequently uses it on a weekend trip to the store. And they know that if they reward her wit h a printed receipt that entitles her to a free cup of coffee, she’ll use it when she comes back again.
Such high level of customer experience personalization is possible only through in-house data management and processing of customer analytics. We live in an age where each customer counts and so we need to know everything about her before we try to design a campaign/ promotional offer – when does she visit the store, what kind of items does she buy, what brands does she prefer and what price is she willing to pay? This information can be analyzed only from data that has been collected from multiple touch-points, and has been analyzed with a specific agenda in mind. Insights on targeting customers and pushing the right buttons can only come from dashboards and analytical solutions that can be constantly tweaked and customized according to a retailer’s specific requirements. Can an outsourced vendor really do this?
In-house customer data management – your data and insights at your pace
To keep up with the pressing competition in the market, retailers need to gain an in-depth understanding of their customers, have the ability to segment them into appropriate groups, target the right customer segment with a specific campaign and measure the effectiveness of a campaign based on the desired set of parameters. To do this, retailers need to invest in a retail analytics product that they can easily plug-in in to their existing architecture and derive the requisite information in a fast, simple and easy manner.
What is required is a customer analytics solution that helps retailers segment their customers, as well as accurately calculate customer lifetime value, detect behavior indicators across seasons and life changes, and monitor transaction data in near real time. With solutions that come with easy-to-use dashboards, retailers can generate real-time reports, get insights on what is happening at the point of sale, when, why and how. In addition to this, retailers can also define their own analysis parameters.
Retailers also require such a tool to come with advanced analytics features that not only conducts customer segmentation but also performs market basket and product affinity analysis, churn analysis and RFM segmentation understand customer behavior more deeply. The better the understanding of the customer, the more effective will the marketing initiatives be.
Does your retail analytics solution provide you with near real-time, actionable insights from customer analytics? Let us know by leaving a comment in the section below!