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The 5 Steps to Unparalleled Customer Loyalty

Posted by Bob Dutcher on Mar 28, 2013, 7:27:00 AM

Loyalty builing blocks1. Identify at-risk customers before they are at-risk

Marketing to customers after they have abandoned your brand is expensive and doesn’t yield great results. It is critical to understand which of your customers will abandon your brand tomorrow, next month or months from now and market to them before they have made the leap.

2. Understand the personal preferences of each at-risk customer

How nice would it be to have a personal shopper pick out products we wanted and deliver them directly to us? For seamless consumer engagement, it’s ideal to understand your consumer’s personal preferences and deliver offers that will engage them and drive greater brand loyalty.

3.  Eliminate sales and retention campaign silos

Standard sales and marketing interactions should contain retention components for at-risk customers. Offering special discounts, promotions or merchandise is a good way to gain loyalty. But remember point #2, that the items offered need to really appeal to the at-risk customer!

4. Identify customers you do not want to retain

That’s right! There are some customers who will never be profitable and predicting who they are can boost your bottom line. An insightful article by the Harvard Business Review, “The Dark Side of Cross-Selling” makes the case that while cross-selling in aggregate is profitable, there are about 1 in 5 unprofitable customers routinely being cross sold to. Profitability metrics should be integrated into all campaigns.

5. Realize customers that are no longer at-risk

To maintain margins, it is important to know individual customers that have dropped off the at-risk customer list, so special loyalty discounting or promotions can be leveraged wisely. To keep their loyalty, you should still anticipate their preferences, so that every offer and interaction can be personalized just for them.

 (Bob Dutcher is VP Marketing at InsightsOne)

Topics: marketing, email marketing, big data, advanced analytics, business insights, business perspective solutions, predictive analytics

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