Sep 08, 2014
Firms face a daunting task in optimizing multiple routes to market. It's just too complicated. "The question of 'which channel should the firm push sales to?' does not have a straightforward answer," says Emory Prof. Sandy Jap. "Simply pushing sales to the most profitable channel overlooks marketing spillovers that may drive very different sales lift patterns in other channels."
At MSI's October 15-16 conference, "Orchestrating Marketing in a B2B Environment," she will describe a practical model to guide multimedia spending in such dynamic environments. The framework, developed with University of Notre Dame Prof. Tom Gilbride, offers insights on the potential profit and sales lifts from driving sales to one channel versus another, increasing profits by 22%-79% in the cell phone provider dataset in their study.
Most firms recognize that channel marketing strategies are critical to firm performance. For example, when Samsung abandoned exclusive deals on their new Galaxy S III, they enabled Verizon, T-Mobile, Sprint, and AT&T to launch the new phone across multiple phone networks simultaneously. This "distribution coup" put Samsung in the #1 spot for cell phone sales.
"The services rendered by channel members not only enhance the product's value, it may well determine the purchase," says Jap. Online marketplaces like eBay bring together far-flung buyers and fragmented supply bases. Big-box retailers offer one-stop shopping across product categories. Dealers provide post-purchase maintenance and support. "For many customers, the product is just the starting point of their total purchase bundle."
In the study, Jap and Gilbride posited that each route to market contributes to a "stock" of channel goodwill that is built over time by different product and service offerings. They developed a sales response model, based on data from a major mobile cell phone provider, that included weekly sales, profitability, and media mix spending for four sales channels—corporate-owned retail, franchise, indirect retail, and telesales. The model also accounted for cross-channel carryover effects of advertising expenditures and advertising stocks in television, print, and radio media.
Model findings offer insights into how channel strategy should be tailored to each market. For example, marketing efforts in the indirect retail channel (which include stores like Best Buy, Target, and Wal-Mart) had the least effect on sales share overall. "This finding quantifies the indirect channel's value relative to the firm's own vertically integrated channels," Jap points out. "This information could be particularly useful when the firm is negotiating channel compensation and structuring trade incentives."
The researchers were surprised to find that the least profitable sales channel -- telesales – actually had the most consistent impact and greatest carryover effect on channel system sales across several markets. This demonstrates the fallacy of simply pushing customers to the most profitable channel.
Since channel strategies are difficult to alter in the short term, the researchers simulate how channel sales would be affected by redistribution of the advertising spend across media forms. "Clearly the mix of channel types in a sales market exhibit differential responsiveness to the ad spend; to the extent that the firm can identify potential media-sales channel synergies, more could be wrung from each dollar spent," Jap said.
They found that the sales lift would be greater across the four sales channels if TV advertising was decreased and reallocated to print and radio in five markets, and spending on TV, radio, and print was increased to historic maximums in three markets. Implementing this "best" policy resulted in a sales channel mix projected to increase average weekly profit by 22%-79% across the markets in the dataset.
Jap notes that the framework can be easily implemented by marketers to provide targets for the optimal mix of advertising expenditures to maximize sales across a multichannel system. Another major advantage of their decision support system is that it requires relatively nominal data. All that is needed is historic multichannel sales volumes and advertising spend. Knowing the individual channel profitabilities helped them better project the bottom-line impact. "In firms where actual marketing channel cost data are available, the model's predictive power would be sharpened even more," Jap said.
As channel strategies become more various and complex, these findings offer the welcome news that marketers can still uncover a path to the best marketing ROI. "Multichannel strategy is a complex task; decision support systems can help firms better leverage these investments."
From "Channel Marketing Stock and Multichannel Optimization," Sandy Jap and Tim Gilbride, Working paper (2014)