Turn leads into gold with marketing attribution

Find out why Web Analytics won’t turn your lead(s) into gold ... and why a two-step approach and predictive analytics will. This blog explains what is marketing attribution really about.

Turning leads into gold is the eternal pursuit of the marketers, like turning inexpensive metals as lead into gold was the Great Work that the Alchemists tried to achieve for centuries. The Alchemists ultimately failed in their quest for a very simple reason: they did not base their approach on facts, but on mystical and arbitrary assumptions. As a marketer, don’t make the same mistake. Do not assess the effectiveness of your marketing efforts based on assumptions and arbitrary models like Last Touch or Linear models from your web analytics tool.

Marketing attribution is about giving credit where it is due and no matter how fancy the custom weighting model used in your Web Analytics platform, assigning credit to marketing touches based solely on presence, frequency and order of touchpoints is wrong. The frequent presence of a touchpoint in the customer journeys is not enough to ensure that this touchpoint will lead to a customer purchase. This is confusing correlation with causation. 

Per definition, any approach which does not integrate the likelihood of a given type of customer to convert independently of the marketing channel will fail at accurately estimating the sales uplift of those marketing channels. This is simply because marketing does not account for 100% of the new sales happening. And marketing will explain a different proportion of the new sales depending on which customer segment you are looking at. For highly loyal customers with an intrinsic high likelihood to purchase, the sales uplift of the marketing channels appearing the most frequently in their journeys might be close to zero.

We all realize that attracting a first-time customer is not the same process as loyal customers repeating sales. So, before starting an attribution modeling exercise, you should:

  1. Evaluate their basic likelihood to purchase independently of your marketing effort,
  2. Only then evaluate the incremental effect of your marketing, on top of this basic likelihood.

This means a TWO-STEP APPROACH because for nearly all your customers, the sum of all your marketing effort can’t account for 100% of the purchase value. Unfortunately, Web Analytics won’t be able to tell you what is the purchase likelihood of a specific customer or customer group and how you should segment your customers before you start doing marketing attribution so that you know that for segment 1, the marketing channels should receive only 20% of the purchase value, for segment 2 only 40%... For this, you need to establish customer profiles based on advanced analytics.

Why is marketing attribution crucial? 

What is your quest as a marketer? Outside your organization, it is certainly about communicating the value of your product or service to customers for the purpose of selling or promoting it. However, in your daily life, you may spend more energy in communicating the value of your marketing activities within your organization.

Why is that? In my experience, our internal quest mostly goes wrong because clicks, registrations, impressions (in other words, our own marketing jargon) are often meaningless outside the marketing department. Because they cannot be linked with the sales metrics driving the whole organization.

Make no mistake, the story about the value of your marketing that hooks the CEOs, should read, ‘Which channel should we best invest in and how much should we invest if we want to achieve a global 10%/20%/50%... increase of our sales next month based on our sales forecast?’ This is crucial in a multi-touch world, where your channels and the interactions of your customers with them are multiplying. You can’t optimize your marketing investments properly unless you can accurately assign credit for the new sales to your channels.

What are the really hot leads within the customer journeys that you are tracking? Certainly not the ones that will convert to Marketing or Sales Qualified Leads but rather the ones that will translate into new sales, into Gold. Attribution, by pointing-out the touchpoints that really count when talking about incremental sales, establishes a behavioral profile, and designates the right leads amongst the usual suspects.

The Two-Steps of the Bottom-Up approach

Customer journeys are made of the sequence of events or touchpoints between our customers and our marketing channels. Digital touchpoints are central in this view, but offline interactions like event registrations, call center interactions, touchpoints where exposure is consistently being tracked in your CRM, might be integrated.

The following Visual Analytics screenshot illustrates part of the most common journeys amongst customers and prospects for a specific timeframe.

This is the ‘What happens’ part of your story, your plot; the customer, your protagonist. Your goal is to understand how the customer changes as a result of a specific customer journey or sequence of touchpoints with your brand. That's what your attribution story is actually about. It is about predicting the likelihood of future purchases as a function of past behaviors, here mainly the touchpoints. You use for this regression techniques such as decision trees, logistic regressions that segment your customers and isolate the ones that will convert because their replicate behavior that led to additional purchases in the past. 

The First Step or establishing a Baseline

The game of marketing investments is about precision. To maximize precision when measuring the sales uplift created by your marketing, we need a first step where you isolate the sales uplift created by all the other factors at your disposal, excluding the marketing part. For existing customers, we can use information about previous purchases to quantify their intrinsic likelihood to purchase. For prospects, we would typically use a global engagement score to quantify their intrinsic likelihood to purchase for the first time.

In the following example, we run a decision tree in Visual Analytics to segment our customers and prospects in function of their likelihood to buy:

  1. On the first chart, the decision tree prioritizes the factors driving likelihood to purchase outside marketing. Factors coming higher in the tree are more important. We have in decreasing order of importance: business segment, type of product purchased, premium flag, total amount, and loyalty score at the bottom.
  2. On the second chart, with the Leaf Diagram, the decision tree distinguishes 20 segments with a different intrinsic likelihood to purchase.

The Second Step: the incremental effect of marketing on new sales

So, for each segment, thanks to our decision tree we have now their own likelihood to purchase without marketing influence, this is our baseline. We include now for each of them the marketing channels to see the incremental effect they have on their baseline our intrinsic likelihood to buy.

The following example shows the results of a logistic regression for the segment with the highest likelihood to purchase without including the marketing impact, in this case a baseline of 10%.
For this segment, we see on the first chart of the following screenshot that Website Engagement, Social Media and Organic Search drive a significant incremental impact on the likelihood to purchase:

  1. If a customer from this segment demonstrates a high website engagement then his likelihood to purchase increases from 10% to 35%.
  2. If a customer from this segment demonstrates a high website engagement AND converted on Social Media then his likelihood to purchase increases from 35% to 75%.

This is a great discovery because we now measure the incremental effect of our marketing in terms of sales uplift. The second take-away in this example is about how accurate we are at identifying our most attractive leads when including marketing activities as well. The top 10% of our marketing leads within this segment are 10 times more likely to convert as compared to randomly targeting the entire segment.

These are our leads turned into gold. This is the second chart of the following screenshot.



With advanced analytics applied to marketing attribution, the marketers might not have discovered the philosopher's stone of the Alchemists, this legendary substance capable of giving immortality to its owner. But with the ability to credit the right marketing channels for their impact on the new sales generated, it seems to me that marketers finally discovered a secret ensuring their prosperity and long life as marketers inside their organizations.

Would you like to know more about creating journeys that matter? This ebook about customer intelligence in the era of data-driven marketing is certainly worth a look.