A goal oriented approach to dynamic conversion value attribution
A GOAL ORIENTED
BY LAURENT MÜLLENDER, 2015
Marketers often ask themselves the following questions:
„How much do I need to invest for additional conversions?“
„How much am I willing to pay for an incremental conversion?“
„I know what my amount of conversions is, but is it good or bad? “
„How can I prioritize and allocate my efforts/budgets between business segment 1 and 2?“
We‘re going to answer these questions by putting a value on a conversion through a goal
What we want to do is to put a value behind a conversion for a given moment in time within a given time frame.
Depending on your goals, some incremental conversions might be more critical than others.
For example, the more distant you are from your conversion goal, the more efforts you will have to put on those to
reach the goal and therefore distance defines priorities.
What we first need to do is to construct a goal curve for a given timeframe. Let‘s start with representing the typical
conversion curve. I suggest looking at data from the last rolling 3 months or (to eliminate a seasonal bias) at a
rolling YoY time frame.
The cumulated amount of conversions for timeframe X could have a shape like this:
1. Representing the
evolution based on
Now that we have the typical conversions distribution for a reference time frame, we can add the goal curve
The goal curve is in fact a transposition of the historical curve, a multiplicator (e.g. „10% increase in conversions“)
applied to the historical curve.
In this case we set a goal of increasing conversions compared to the reference time frame. The goal curve could
also be below the reference curve if we foresee a decrease in conversions.
For the sake of simplicity we‘ll assume an increase.
2. Representing the
Now we can place observed conversion levels (summed up conversions) on the graph. The distance of these
observed conversions to the ideal goal line is the conversion value. It tells you how much effort is needed to reach
the goal, how important incremental conversions are for you. The bigger the distance, the more the incremental
conversions are important.
Note that here in this example, conversion growth slows down over time. That can for instance be a seasonal
characteristic or a campaign which is slackening.
The second conversion point on the right indicates a big issue: we are far from reaching the goals and considering
the slow growth to expect until the end of the time frame, we will surely not reach the goal even if it has a high
conversion value (distance).
3. Mapping observed
This model will help you value, prioritize and optimize your efforts.
This performance based approach is robust for both orders and leads: since it assigns a value to a
conversion, it can also be used for conversions which do not have per se a monetary value.
You can use this for ad hoc analysis or for ongoing and automated analysis on rolling data. I
recommend the latter as it will allow real time optimization.
Also, segment your conversions on relevant criteria for your business (products, categories,
regions,…) to allow cross segment optimization: you can have a conversion value model for
product line A and one for product line B and then determine how to allocate efforts between both
based on this model.
Better controlling and control of marketing measures and investments.
Better Budgeting based on performance and facts.
Use the conversion value in your Adwords Campaigns as Conversion Value
Combine this information with your DMP data to adjust real time bids of campaigns