How To Get Smart(er) With Conversion Tracking
Taking consumer lifetime value into account allows performance marketers to manage more volume at a higher cost per acquisition (CPA) or lower return on investment (ROI). If $1 of revenue at the time of conversion leads to an additional $1 of revenue ($2 total) down the road then breakeven for marketing is 0.5 ROI or […]
Taking consumer lifetime value into account allows performance marketers to manage more volume at a higher cost per acquisition (CPA) or lower return on investment (ROI). If $1 of revenue at the time of conversion leads to an additional $1 of revenue ($2 total) down the road then breakeven for marketing is 0.5 ROI or a CPA equal to 50% of the average order value (AOV) and anything better is money in the bank.
However, simply multiplying the conversion value by the perceived lifetime value (LTV) can provide convoluted and misleading metrics because we cannot operate under the assumption that all conversions come from new users.
If you’ve ever worked for, with, or been funded by a venture capitalist, then you’ve probably been tasked with new user acquisition as your primary metric for success. There is merit to the approach, even if it leads to short-term “unprofitable” metrics – which go against the instincts of performance marketers.
Willingness to pay a lot for new users to buy your product in conjunction with a sticky product will yield long-term profits. But what happens when the long term becomes the present day? It is possible to maintain unprofitable margins indefinitely or does something have to change?
With any sticky product, at a certain point in time a significant percentage of customers become repeat customers. Uninformed marketers do not differentiate between new and repeat transactions leading to a skewed perception of the value of a transaction.
To clarify – repeat transactions are defined as a transaction from a user who has previously executed a transaction on your site, regardless of the original acquisition channel.
Applying a lifetime value multiplier to all conversions skews the perceived value of transactions because some transactions are from new customers but many come from repeat customers; repeat transactions which have already been factored into the LTV model applied at the time of their first transaction.
As a result, we cannot apply the same lifetime value multiplier to all conversions – we need to isolate transactions coming from new users versus repeat users and apply unique lifetime value multipliers.
As for the unique lifetime value multipliers, new transaction values are multiplied by the calculated channel specific LTV whereas repeat transactions should be disregarded as they are theoretically accounted for in the initial lifetime value multiplier applied at the time of the users first purchase.
I Get It…So How Do I Do It?
Most analytics platforms and simple cookie / pixel conversion systems (AdWords conversion tracking, AdCenter, Facebook, Google Analytics, etc) cannot differentiate between a new user and a repeat user transaction. This is because existing user data is generally stored within an internal database – data which is rarely [if ever] available at the time of purchase for a real time cross reference to populate in the pixel at the time of transaction.
More flexible systems allow for latent updates to order values. For example, after cross-referencing order IDs with the existing customer database, you can send a daily data feed with the Order IDs as the primary dimension and the updated revenue values or, if your platform is even more flexible, you can replicate all transactions to a second conversion tracker and zero out repeat transactions so you are able to retain both sets of numbers:
But I don’t want to spend a lot of money on a fancy solution…
If you don’t have access to a platform capable of incorporating latent data, it’s possible to build a dashboard via Access and/or Excel by merging multiple data sets to deliver a similar result. In all transparency, this isn’t as easy at it sounds, but it’s possible and yields actionable results.
While an offline report is not easily incorporated into a bid management solution or analytics platform, it can help you understand the new vs returning order distribution by channel / campaign / placement:
The purpose of this exercise is to ensure that your marketing efforts are focused on identifying, educating, and converting new, potentially high lifetime value users rather than driving repeat conversions. Without it, you become liable for overvaluing the effectiveness of your campaigns, a problem which worsens over time as perceived lifetime value multipliers exaggerate the intrinsic value of performance marketing.
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