Understanding Attribution’s Contribution To Customer Quality
Cross channel attribution management provides the benefit of insights that can inform marketing strategies by revealing the true impact that every marketing tactic, campaign and channel has on your overall marketing success. It does this by scientifically calculating the impact that every marketing touchpoint experienced by your prospects has on achieving a specific marketing goal […]
Cross channel attribution management provides the benefit of insights that can inform marketing strategies by revealing the true impact that every marketing tactic, campaign and channel has on your overall marketing success.
It does this by scientifically calculating the impact that every marketing touchpoint experienced by your prospects has on achieving a specific marketing goal – such as conversions, revenue, return on advertising spend (ROAS), etc.
But where the attribution process ends for most marketers is with the acquisition of a new customer and looking solely at media metrics – failing to extend the attribution exercise to include the longer term enterprise value or quality of that newly acquired customer.
Look At Value Beyond The Initial Transaction
Suppose that after performing attribution, it was revealed that a given search engine actually produced 1,000 conversions at a given ROAS for a specific keyword for the initial transaction that it produced.
Meanwhile, another search engine produced just 300 conversions for the same keyword at a given ROAS on that initial transaction.
If your analysis stopped there, it would be pretty simple math to determine which search engine to channel future budget to for that given keyword (assuming sufficient search inventory existed for either option).
But if this attribution exercise included looking at the some “customer quality metrics” that were revealed over time about the 1,000 customers compared to the 300 customers, very different investment decisions may result.
What if you went a step further and looked at different metrics associated with those 1,000 customers and those 300 customers at three months, six months and 12 months after that initial transaction?
For example, the following metrics might be very telling about the quality of your customer:
- How many have made subsequent purchases and how many were one-shot wonders?
- How many are still active subscribers and how many has attrition eliminated – requiring you to now have to spend acquisition dollars to “re-activate?”
- How many have bought high-value (to you) products?
- How much revenue have they produced and what is their predicted revenue contribution within an appropriate customer segment?
- What is their average lifetime value (LTV) taking into account profitability or influence from a social or viral perspective?
After analyzing these additional metrics the results may surprise you, as it’s entirely possible the search engine that produced only 300 conversions might have resulted in more quality customers over time.
Feed Customer Quality Metrics Back Into Attribution
The example above obviously extends beyond search to online display ads or any other media channel – as well as across various channels – but the point is that once the quality metrics above have been collected, they can be fed back into your attribution engine.
Then they can be used as a success attribute to predict and ultimately optimize future marketing performance based on not just the value of the first transaction and your ability to achieve your acquisition goals, but to optimize for long term ROAS, ROI and enterprise Lifetime value (LTV).
This is a great start at taking the attribution process to the next level, but you owe it to yourself to not stop here. After all, at this point you’re only looking at two dimensions of your success: the media metrics associated with producing a new customer and the media metrics associated with producing the highest quality customers.
What’s next is adding demographic/audience attributes of those customers to the attribution process.
What Else Produces Highest Quality Customers?
By either collecting age, income, geography, gender, and other demographic data directly from your customers, or by obtaining it from third parties like Exelate, BlueKai, Acxiom or Experian and feeding it into the attribution process, you can not only produce insights on how to optimize for the media tactics that produce the highest quality customers, but use those media tactics to target prospects with the demographic traits associated with your highest quality customers.
Attribution also provides insight into the media consumption behavior of the desired audience by providing insight into content by publisher consumption.
But the key is attribution. The multi-dimensional nature of attribution enables you to analyze your marketing success across an unlimited number of stimuli, response metrics and customer attributes to produce a scientifically valid set of metrics for what truly contributed to your success across your entire marketing portfolio.
By adding the dimensions of long-term customer quality, as well as customer demographic attributes, you truly elevate your attribution efforts to best-of-breed status.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.