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# A goal oriented approach to dynamic conversion value attribution

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A model to dynamically attribute a value to conversions in order to optimize marketing programs.

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### A goal oriented approach to dynamic conversion value attribution

1. 1. A GOAL ORIENTED APPROACH TO DYNAMIC CONVERSION VALUE ATTRIBUTION BY LAURENT MÜLLENDER, 2015
2. 2. NECESSITY OF CONVERSION VALUATION 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 oriented approach.
3. 3. CONVERSION VALUATION PRINCIPLE (1/3) 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: Conversions Time 1. Representing the typical conversions evolution based on historical data
4. 4. CONVERSION VALUATION PRINCIPLE (2/3) Now that we have the typical conversions distribution for a reference time frame, we can add the goal curve (green). 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. Conversions Time 2. Representing the goals curve
5. 5. CONVERSION VALUATION PRINCIPLE (3/3) 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). Conversions Time 3. Mapping observed conversions X X