Mobile Shopper Marketing

Mobile Shopper Marketing

Michael Quinn, the former Chief Strategist & SVP of Marketing at Premier Retail Network (PRN), wrote an interesting post on his blog entitled “Mobile Shopper Marketing — Who Will Win and Why.” In that post he examined whether the retailer or the brand marketers (aka manufacturers) would win control over “mobile shopper marketing.”

His post, a worthwhile read, postulated two scenarios that would predict the retailers’ control of the mobile space. Scenario 1 proposed that a large digital marketing provider such as Google would build a platform that would span all of the large retailer’s digital marketing platforms to work as — as best as I can determine — a super aggregator of product information and marketing promotions. Scenario 2 proposed that “killer mobile app’s” like Shopkick or Cellfire would enable retailers to market to the shopper via their mobile phone.

While both of these scenarios have merit and will be certainly be employed in one form or another, in reality they tend to be “old school” in their scope and don’t truly recognize the full potential that mobile represents. What do I mean by “old school”? I mean these scenarios are just new extensions of old ways of doing business, e.g. product promotions (couponing) via a different form factor (the mobile device). What the new world of mobile offers is a holistic (the emphasis is on holistic), context-sensitive, location-centric approach to marketing based upon a consumer’s past cross-category buying habits. But what would this model look like and how could it brought to reality?

The best way to understand the “holistic” model is to consider a third scenario. In this scenario, consider online retailers, e.g. Amazon and eBay. They not only know a customer’s cross-category purchase behaviors, but they also know their browsing/shopping patterns. They also possess the analytic and predictive modeling capabilities to forecast what the consumer is likely to purchase next.

What the Amazon’s and eBay’s don’t have is a connection with location
relevance that mobile brings. What does that mean? It means they know what you’ve purchased (again, across product categories), they know what you’re likely to purchase next (especially if presented with the right offer), but they have no way to leverage your location (i.e. mobile) to take advantage of that insight.

So, what does that mean? It means that the Amazon’s of the world benefit by forming alliances with traditional brick and mortar companies to extend their real-time, location-centric reach. Consider this model:

    I, Joe Consumer, have recently bought a Canon digital SLR camera on Amazon. Unbeknownst to me, Amazon has formed a relationship with Best Buy (hypothetical of course) and they’ve integrated (through an intermediary) with Best Buy’s inventory systems. While out running errands, I launch my shopping app (not necessarily Amazon branded), it determines my location and reports it to Amazon. Amazon determines that I’m near a Best Buy. Amazon’s relationship w/ Best Buy provides for Best Buy to deliver a special offer on products when I’m in the proximity of one of their stores. Amazon checks its marketing systems to determine what I’m likely to buy based on past purchase and browsing habits. Amazon determines that I’m likely to buy a case and lens for my Canon camera. Amazon checks the availability of case/lens inventory at the nearby Best Buy location. Amazon determines that the target products are in stock and makes the suggestion, via the shopping app, to check out Best Buy for special pricing on my particular camera case and lens. I go to the Best Buy and buy the product. Best Buy records/accounts for the transaction and records a referral/transaction fee due to Amazon. Amazon records the purchase, which further feeds their analytic data. The manufacture (i.e. Canon in this case) subsidizes the transaction.

The preceding scenario suggests that the online retailer has more cross-category purchase data and better analytics on me than the brink and mortar retailer — especially the specialty store. It also suggests that this analytic information is best leveraged when combined with mobile and supported via a broad base of brick and mortar retailers.

So would the brick and mortar guys buy-off on this type of model? It would seem that they would because it drives traffic to their store based upon objective analytic information and not just randomly placed coupons. It would also seem logical that they would adopt a solution that doesn’t require the consumer to radically change their purchasing behavior, e.g. “checking in” or photographing products and barcodes.


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