In any customer facing business, the channels used to reach out to your customer as well as the channels your customer use to consume your products and services have a strong correlation with overall profitability. 

From the B2C perspective, advertisements, stores, online, mailers, charity, etc. are different ways of reminding customers about your offerings. From a C2B perspective, again, stores, online, home delivery orders, etc. are ways in which consumers consume your products. 

However, the key here is to understand which customer prefers which B2C and which C2B channel. Right-Targeting Customers is as important as Targeting Right Customers! Someone who spends 14 hours a day in front of his computer and has no time to go to a store 5 days a week may prefer a home delivery channel. On the other hand, a student in a college is only interested in the bargain channel, irrespective of the inconveniences, maybe. This report also mentions how retailers need to manage their investments across channel against the scale and timing of their expected return. I would go beyond Ron’s Right Channeling [read post] to include all aspects of targeting under the concept of Right-Targeting. Having said that, I agree that today’s world is about multi-channel customers, and the need of the hour is to optimize channel returns, rather than just channel re-alignment/phase-out. 

Targeting Right Customers- Its equally important is to understand how channel profitability gets affected if you are not targeting the right customer. For instance, Wal-Mart, even with its Everyday Low Prices (EDLP), must be making money on some products/ some SKUs and these would drive the overall positive profitability. However, what if your customers are not buying your profitable SKUs? What if the draw that brings them there is not luring them to buy more? What if there is no up sell/cross-sell/bundling that happens there? And suddenly the business realizes that channel profitability is coming under immense pressure! (One of our earlier posts tries to answer the question of market basket analysis and product bundling). 

Re-Targeting - And last but not the least– taking the difficult decision of phasing a channel out. If it’s not generating any returns (directly or indirectly), the business needs to reconsider the cost of the channel. But what about retaining those customers who are loyal to the channel and have helped you get some mileage out of it? They need to be Re-targeted with a new offering/communication. Traditional retargeting refers to targeting customers who did not convert the last time, though!

This report (PDF) here talks about issues to be kept in mind when moving customers from one channel to another. I am sure Kevin would want to talk about Multi-channel customers being better than single channel customers, and without refuting his argument I would classify my argument as being restricted to customers that are being phased out of a channel. This example demonstrates one case where the retailer has effectively leveraged multiple channels over a period of time by effective use of catalogs and internet channel. 

In Summary

• Right Targeting – Know your customer. Cater to their needs through their preferred channel. It increases the share of wallet, as well as longevity of the customer
• Targeting Right – Pick your customers for each channel-product combination well. Know what and how you are selling and who will buy it.
• Re-Targeting – If it’s imperative that you move away from a particular channel, think about retaining your loyal channel customers. A little caring goes a long way in creating customer loyalty.

The qualifying argument behind all this is that if you are thinking about channel optimization, it needs to be a more concerted discussion based on your strategy/business objective, your data, your needs and your concerns. What we know for sure is that strong data analytics is known to help not only Targeting Right (which is the most common application), but Right Targeting, as well as Re-Targeting.

Ron’s post made me think about the implications of this suggestion on the global banking system. Getting a dynamic price optimization algorithm at a relationship level in place requires an integrated view of the customer.

Almost every bank that I’ve worked with or have talked to, suffers from the problem of disintegrated views, LOBs competing amongst each other, and the customer being valued at the product level and not the relationship net worth level. What’s surprising is that every bank is aware of this problem, is trying to address it in its own way, and still far from being successful.

Ron talks about the futility of this pursuit and the importance of Loyalty Programs in achieving it. Let me look at another side of the story – The strategic focus required for solving this problem. Banks are either sales focused, or profitability focused.

Sales focused banks play the volume game with hundreds and thousands of cards getting shipped every day to unsuspecting customers. The same customer may have a silver, gold, platinum card from the same bank. The idea is to carve out a bigger and bigger share of the wallet without getting bogged down by the profitability levels, as long as even marginal amounts are being made. The same customers are being approached for mortgages, auto-loans, refinancing schemes, personal loans, etc. The pricing of each of these products is done individually, and I mean “individually” at product level – each product is priced separately, The debate is around moving to each individual getting priced separately for her/his bouquet of products.

Profitability focused banks operate on the P&Ls and margin levels for each product. They keep the back-end and front-end of each of their products separated. There is positive money and higher margin, but not a lot of it (in some cases, there might be a lot of money in niche operating areas). However, at some point all such players realize that scale comes from the masses. A seemingly premium American Express card gets offered free for a lifetime in some of the developing countries.

Now, having said that there are two kinds of banks, both of them eventually will try to move in one direction – the integrated view of the customer followed by a relationship management approach. Loyalty programs may help get more data and act as an incentive for customers to proactively get their unified integrated presence in the bank databases. However, loyalty programs are still a piece-meal solution. The effort required is higher, turnaround times longer, and vigilance is incremental. Changes need to be introduced gradually and their effect/success needs to be monitored.

Compare that to the “break the bank apart” module before reorganizing it. The upfront investment is higher, the complexities overwhelming and the implementation time can be long initially. What the banks need to realize is that the investment required to upgrade to an integrated view of the customers is a strategic investment to be amortized over several years. Any bank ready to take the pains and go through the organizational and technical barriers will find itself way ahead of its competition. The proof of this lies in the gradual advent of Direct Banking, which forces an integrated view on the customers for all the products offered since there aren’t multiple human-to-human touch-points.

At Diamond, one of our key strengths has been the ability to think about, create plans for, and help our client implement both. Helping client redefine their data systems, architecture, program managing it to successful implementation, followed by the ability to create a relationship view and management approach. Our analytics approach has been geared at looking not just at the problem at hand (increasing sales, improving profitability) but also at increasing the impact of the business for overall success.

One of the most popular search term that brings people to this blog is “marimekko chart”. People are mostly looking for a template to easily build a marimekko charts and stumble upon our related postings on churn and a new way to represent at marimekko charts. In order not to disappoint them, I am adding a nifty excel template (Mekko maker.xls) which makes creating standard marimekko charts a breeze.

Two news-articles, talking about the different aspects of choice as explained by behavioral economics.

Washington Post (via Seth) reporting about how having a third candidate in an election can actually be better for the front-runners, in what is known as the decoy effect in behavioral economics.

third candidates regularly have the unintended effect of making one of the front-runners look better than before in the minds of undecided voters.

Wall Street Journal article (subscription required) on Nike’s new initiative to simplify its product lines and focus on its most popular t-shirt designs, to ensure that consumers do not have decision paralysis.

the company has flooded stores with thousands of variations on its famous “Swoosh” products, resulting in a vast array of products that were expensive to manufacture and keep track of and that often confused shoppers.

Choice (or lack of it) is an interesting area to apply data analytics. It is important for a company to understand how to present choices, and help a customer navigate through them effectively, from the brand awareness, purchase, through cross-sell and retention lifecycle.

Look out for more on this topic in future.

Photo courtesy Michael_L