Add Analytics, Reduce Marketing Waste

With the intention of reaching as many customers as possible, companies often execute mass marketing campaigns that prove to be costly and ineffective, sometimes even backfiring when they target customers with the wrong message. Not only will irrelevant emails make customers less likely to pay attention to future messages from that company, but in the worst case scenario, they could even annoy customers and drive them away. Reaching out to the right customers with the right message is critical to the success of any marketing campaign, and by incorporating customer analytics into their strategy, marketers are able to target only the right customers, in turn ensuring a higher campaign ROI and reducing the amount of wasted resources.Segmenting Your Customer BaseAnalytic customer intelligence tools help marketers enhance and tailor their marketing campaigns in several ways. Uplift modeling, a relatively new technique, is an analytic approach to marketing that predicts the difference that a marketer's actions will make to the behavior of customers, as opposed to predicting customer actions that would have happened with or without the marketing treatment. Uplift enables an organization to segment its customers based on a prediction of how each segment will react to a marketing outreach when compared to a control group. Uplift modeling enables marketers to identify and focus on contacting only those who will react positively to their message, weeding out the customers who will buy anyway, will never buy or could react negatively. Uplift modeling divides your marketing audience into four segments: Sure Things, Lost Causes, Sleeping Dogs and Persuadables. "Sure Things" are those customers who will buy (or renew) regardless of whether you target them with the current campaign, while "Lost Causes" will never buy regardless of anything you do. "Sleeping Dogs" are customers who are likely to react negatively to a marketing campaign, perhaps taking their business elsewhere, and "Persuadables," are those who react to your campaign in just the way you hope, by buying (or renewing), but are the customers who wouldn't have done so had you not targeted them.Reduce Marketing CostsBy helping companies focus their marketing campaigns on reaching only the "persuadables," Uplift modeling enables organizations to eliminate the wasted resources associated with reaching out to the wrong customers. Using the insight provided through uplift modeling to target only those likely to respond also helps marketers maximize the impact of their campaigns and significantly increase their campaign ROI. For example, after integrating uplift modeling into its marketing strategy, one Fortune 50 retail electronics company was able to increase monthly catalog revenue by $2.5M through reaching more "Persuadables" and allowing the "Sure Things" to buy without the need for a catalog. In another example, U.S. Bank saves $400,000 per campaign using uplift modeling to identify and stop sending mailings to those who would have purchased anyway.In the world of marketing, relevant, targeted campaigns will always yield better results than broad, blanket campaigns, especially when targeting the wrong customers can be detrimental to sales. By incorporating uplift modeling, fueled by intelligent analytics, into their campaigns, marketers can ensure that they're targeting the right customers, while avoiding those who will ignore their outreach or find it annoying. Enhancing your marketing strategy with a more targeted approach not only improves the success of your campaign by increasing incremental sales, but it also greatly reduces your costs.Mark Smith is executive vice president of sales and marketing at Portrait Software, a leading provider of customer interaction optimization software. Portrait enables organizations to engage with each of their customers as individuals, resulting in improved customer profitability, increased retention, reduced risk and outstanding customer experiences.

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Add Analytics, Reduce Marketing Waste

Mark Smith

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Mark Smith