A set of whitepapers for the executive who wants to leverage the data to make smart marketing investments:

1. Identifying attractive markets and understanding your customers
2. Increasing online sales
3. Focusing on profitable distribution partners
4. Improve customer experience through call center data
5. Retaining your customers

Two interesting statements from a recent report in American Banker (password required):

• In the decade from 1996 through 2005, banks added an average of 1,484 branches a year
• There is a direct correlation between the location of a branch and its success or failure in amassing deposits

Going by this, retail banks could certainly use the optimization methodology, we used recently (see related post) to map branch location to ‘desirable customer segments, to increase average deposit per branch

Note, the key word in the above question is ‘profitable’

Companies using multiple channels and/or multiple partners to sell their products usually track gross sales numbers to compare channel/partner performances. However, a top-line metric approach can be misleading. More importantly, getting to an accurate bottom-line view is not extremely challenging and does not require any significant IT investment or business intelligence tools.

Recently, we helped one of our clients to understand the profitability of their partnerships by taking a lifetime view of revenues and service costs of customers, acquired from the partner channel. The challenge we faced was in forecasting the attrition rate for each partner, to which our creative solution was to cluster similar partners together and calculate an average lifetime of each of the clusters.

In addition to lifetime revenues and service costs, we determined the cost of partner acquisition and maintenance (legal costs, business development and audit costs) along with the direct campaign related costs – to estimate a ‘true’ customer acquisition cost. An additional filter was added to control for variability of partner performance over multiple campaigns.

We discovered (to everyone’s surprise) that 86% of the client’s partners were unprofitable. More surprising was the fact that all these partners used to regularly pass the client finance department’s screening criteria as their metrics were focused on short-term benefits and not on ‘true’ lifetime value. Diamond’s analytical approach helped to fix the client’s issues and put the channel back on path to profitability (increased channel NPV by 190%)

It is interesting to note, that we did our entire analysis without requiring any support from client’s IT group. We directly queried client’s billing and other marketing databases to get the relevant data. Considering, how easy it is to perform the analysis; it is surprising that most companies do not have a good grasp of their partners in terms of profitability.

Our findings and more details of our methodology are documented in the whitepaper, Profitable Channels: The Right Metrics Make All the Difference

When Scottish hotelier Charles Forte was asked about the secret of success of his hotels, he is reputed to have said, “Location, location and location.” . This credo also seems to apply to almost all companies who do some form of brick and mortar distribution. Be it a retailer who wants to improve its productivity or companies who want to optimize the spend on distribution and associated trade marketing.

Companies have historically focused on removing inefficiencies from supply chains by optimizing inventory and logistics. Store location which falls at the intersection of operations research and marketing has only recently received some focus. The major challenge in being good at locating new stores or evaluating the future potential of existing stores, is integrating the customer segmentation strategy with the distribution data.

We recently helped a client to evaluate the retail distribution strategy and came across this problem. We solved this problem by creating a market potential index, by identifying the concentration of client’s most profitable customer segments, for every county within client’s footprint. We could then map the number of points of sale (POS) per each county to evaluate whether the client stores are in ‘desirable’ locations.

We found that 24% of client’s retail investments were made in locations that were less than desirable, and realignment of POS to desirable locations would save the company millions of dollars a year, even by conservative estimates