Quadrant Chart for Analytics Versus Multichannel Sophistication (Part III)

A recent post highlighted the central idea behind the book Competing on Analytics: Namely, many companies employ analytics (business intelligence) merely in a tactical role, i.e. for improving ROI, while a few others use analytics so cleverly that they become the basis of their differentiation.

Then, another post had a similar observation about the way that companies use multichannel marketing. Namely, for most companies the existence of multiple marketing/business channels is just the way things are done in their industry. Yet a few other companies are able to use channels so cleverly that they become the basis of their differentiation.

Well, given those two dimensions, analytics vs. multichannel marketing, it became irresistible to me to see what happens when we juxtapose both in a quadrant chart. Is there anything to be learned from companies employing both of these in either a tactical fashion or as a strategy that forms the basis of their competition?

Here we go.

In the chart below, the use of analytics, as a tactic vs. a strategy, forms the Y axis. The X axis stands for the use of multiple business channels as a mere tactic vs. as a strategic differentiator.

Let’s place some companies that we all know on this chart.

The old Blockbuster was arguably in Quadrant I, i.e. there was no differentiating use of business intelligence nor multiple channels that an outsider could spot.

In came Netflix as a competitor in Quadrant II. Netflix used the online channel as a differentiator, namely a video store that offered infinitely more choice than any Blockbuster branch ever could. Plus better terms on top.

Blockbuster countered by matching Netflix’s terms and capability for rent online / deliver by mail. But in addition Blockbuster also added the weight of their 5000+ stores into the battle. Now customers could rent online as with Netflix but also return and rent in stores on the spot. That moved Blockbuster also into Quadrant II, competing on channels.

NetFlix has an Ace up their sleeve though. Namely, as discussed in the book Competing on Analytics, Netflix is honing their analytics behind movie recommendations. The analytics for providing more relevant movie recommendations are expected to become the basis on which NetFlix will now compete with BlockBuster going forward. At the same time its online channel advantage is being matched and therefore eliminated. That moves NetFlix from Quadrant II to III.

Can either company move into Quadrant IV where they differentiate on both the basis of analytics AND the basis of channels? How?

Note that if Netflix merged with, say, Safeway, to match Blockbuster’s store channel strategy, it would not move Netflix into Quadrant IV. Rather, the store channel would become a non-differentiator for either company. Blockbuster would move back into Quadrant I while Netflix would stay in III, at least until Blockbuster can match its movie recommendations. The take away from this observation is that the Quadrant is not just determined by a company’s own actions but also those of its competitors.

So, can you think of a way that one of these companies could cross into Quadrant IV before the other one does?

For Netflix it would require a way to make use of channel advantage in a way that Blockbuster can’t immediately match. For instance, this could be to pass on to its customers the cost savings from having no brick & mortar stores to maintain.

For Blockbuster it would require a way to use analytics in a way that Netflix can’t immediately match. Maybe some kind of analytics on what is going on in their stores? For example, market basket analysis to recommend the best candy that goes with each movie? (Just kidding).

Akin Arikan, the author of Multichannel Marketing: Metrics and Methods for On and Offline Success, is a senior manager for Internet marketing at Unica Corp. with responsibility for ensuring customer satisfaction with Unica's web analytics and Internet marketing solutions. Akin has been working with web analytics practitioners since 1999.