Business Intelligence and In-Store Marketing

There are many ways to measure in-store consumer marketing activity and yes, the technology, measurement processes and business decision-making activities based on point-of-sale shopper data is rapidly changing. Several key thoughts: 1) Point-of-Sale (POS) / Scan Data is valuable...where available. Not all major retailers track, manage and share POS data with consumer goods manufacturers or other business partners.  Where the data is collected and managed, it is not always clean and requires data cleansing efforts to get it to a point where it can be used to drive decisions in marketing, ad, supply chain and production business processes.  Where available, POS data can be extremely valuable.  With a clear picture of the "consumer" or "shopper", manufacturers and retailers can better plan product placement, pricing, back-room supply, improve forecasting, reduce out-of-stocks and drive cross-sell / up-sell campaigns.

2) Changing times demand better access to data and business intelligence. With the rapidly shifting economy - and therefore consumer preference landscape - access to decision-support data is more important now than ever.  Ad and display data is critical to enabling marketing decisions while sell-thru data like POS and scan data enable more efficient supply chain and sales planning processes.  Business intelligence technology solutions (and therefore investments) are top-of-mind for many CIO's looking to make sense of large volumes of consumer demand data in order to support business unit investment decisions around ad dollars, promotion planning, etc.

3) Several options exist for measuring shopper marketing data. First, some retailers track in-store purchase data and are able to share that data with data aggregators or manufacturers.  Second, firms like Nielsen and IRI collect in-store execution activity (ads, displays, demographics, etc.) and this data is available for purchase.  This data typically lags by a few weeks but is useful in making investment decisions once matched up with actual sales data.

4) Timing of Demand Signal and Activity Data is Critical for Business Decisions. The challenge with using in-store marketing data is the timing of receipt of the data.  For real-time decisions to be made in the online and social media spaces, data must be delivered or made available in a frequent fashion - cleansed and made available in decision-support tools.  Syndicated data can be useful for future promotion planning but is not useful for real-time execution of campaigns due to the latency (days / weeks).