The Blind Spots of Traditional Retail Data and Analytics

A few weeks back, we published our new whitepaper, The Golden Age of eCommerce & How Analytics Hold the Key to Brands’ Long-Term Success.

I wanted to illuminate a key section of the whitepaper that can provide perspective on the shifting retail landscape on how brands should take advantage of leading indicators of consumer demand to spark data-driven business agility.

Diminishing Value of Traditional Retail Data and Analytics

The capabilities and mindset required for brands to win eCommerce are distinct from the those that worked well in the B&M world — starting with data. Historically, brands have relied on traditional sources of retail data to understand consumption trends. Nielsen, for example, has become known as the great aggregator of retail data, collecting point-of-sale (POS) information from more than 900,000 stores worldwide and offering brands with insights into market share, competitive sales volumes, pricing, and more.

While Nielsen, and similar companies like IRI and SPINS, have been critically important for brands to gain a competitive advantage in the past, there are several downsides to relying solely on B&M market intelligence in today’s online-driven landscape:

1.   B&M retail data is reported from several months in the past. In a B&M-only model, this made sense. Business planning was typically done annually, with periodic reviews of sales performance. However, this same process does not translate to eCommerce where brands must manage their digital shelf in real-time to improve execution tactics, or risk losing significant sales.

2.   B&M retail data is a weak indicator of trends. Significant blind spots of B&M retail data make it challenging for brands to gain an accurate measure of consumer demand and catch market trends early.

The first blind spot is that data is limited to what will actually fit on the store shelf. Category managers typically select an assortment of products that are proven winners from past seasons, while de-prioritizing seemingly less popular preferences and newer brands. This means that by the time most trending products make it to the store shelf (i.e., are included in B&M retail data), they are no longer trends but mainstream items with a healthy dose of competitors.

The second blind spot is that B&M data lacks products coming from digitally native brands. These brands are proving time-and-again to be formidable players with significant market share and should be tracked diligently to understand complete category dynamics.

Wondering what you can do to cure these blind spots?

We believe that eCommerce Data and Analytics are the key to unlocking a competitive advantage.The shift to online retail has long been in the cards, and the COVID-19 pandemic only intensified the inevitable. B&M stores are concurrently dwindling and evolving their role in the customer journey.

Learn more about this approach by downloading a copy of our whitepaper here.