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Customer lifetime value: Optimize that online spend

As with everything, there are best practices when it comes to optimizing online marketing spend for highest customer lifetime value, revenue, or profit.

It’s a three-step process.

First, know your lifetime customer value (LTV) by source, by individual affiliate, ad variation, keyword, and whatever other level of granularity will enable you to best optimize ROI on marketing spend.

Second, have LTV data by source handy when you’re making marketing spend decisions or optimizing campaigns.

Third, make sure to have an LTV online marketing optimization strategy. This step is a little more involved:

  • You’ll need a plan for how much you can scale each channel without diminishing returns. For example, some Internet retailers find a few keywords to be phenomenally profitable, but they can only scale those terms, permutations of those terms, and keywords related to those terms so much without declining their results. Often, while a portion of a search or display media campaign underperforms the rest of the campaign in LTV, the company still needs the volume from the other keywords in order to hit revenue metrics.
  • Know the frequency of which LTV data batches are available for optimization. Some companies get daily LTV data and can track variations in finite time periods. Other companies only batch LTV data quarterly. Therefore ,new merchandising mixes or first-time media buys with a new source—such as a new display media campaign, or an initial media buy with a group buy site—will not yield data until the close of the quarter. The most sophisticated online marketers we see know the frequency in which their customers make repeat purchases, site visits ,or other metrics that they track and optimize.
  • Take note of your most important metrics and how they relate to each other. Many online marketers have their own methodologies for optimizing campaigns. Some reallocate spend every week or every month; other take on the task quarterly based on their best/worst performers. Still others know that on average their customers make their first repurchase 30 days out and use this information accordingly to assess the success of new or existing customer acquisition channels—particularly new channels—before scaling spend further.
  • Remember: Shorter cycle-time CLV optimization is best. If you know, for example, that repurchasing patterns or churn rate by source are fairly consistent by source after 90 days, then use 90-day CLV as your optimization metric and track correlations between initial purchase CLV, first 30 day purchase CLV, and 90 day CLV. If your CLV data by source batches weekly, you can optimize first in five weeks and then again in 13 weeks.

To some degree, online marketers are limited in their performance by their access to data and the sophistication of their company’s data. At the same time, the more online marketer, can paint the vision for their company of what success looks like, the more likely they are to be able to work successfully in that environment.

Ted Bockius is director of marketing at RJMetrics. More from Bockius in Direct by Design.

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