Marketing attribution: Web analytics won’t work, but predictive analytics wi

Marketing attribution: Web analytics won’t work

Turning leads into gold is the eternal pursuit of the marketers, like turning inexpensive metals as lead into gold was the Great Work that 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.

Don’t assess the effectiveness of your marketing efforts based on assumptions and arbitrary models like last-touch attribution 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.

Based on this  definition, any approach that does not consider the likelihood of a given customer type to convert independently of the marketing channel will fail to accurately estimate the sales uplift of those marketing channels.   This is because marketing simply does not account for 100 percent of new sales. And marketing will account for a different proportion of the new sales depending on which customer segment you are looking at. For example, highly loyal customers with a high likelihood to purchase are less likely to be affected by marketing on any of their usual channels.

Two steps toward better marketing attribution Attracting a first-time customer is not the same process as loyal customers repeating sales. So, before starting an attribution modeling exercise, you should evaluate: Their likelihood to purchase independently of your marketing efforts. The incremental effect of your marketing, on top of this likelihood. This means you’ll want to implement a two-step approach because for nearly all your customers, the sum of your marketing effort won’t account for 100 percent of the purchase value.

Unfortunately, web analytics won’t be able to tell you the purchase likelihood of a specific customer or customer group, or how you should segment your customers before employing marketing attribution.  If you want to know that for Segment A, the marketing channels should receive only 20 percent discount, for segment B only 40 percent. For this, you need to establish customer profiles based on advanced analytics.

Your mission as a marketer is communicating the value of your product or service to customers for the purpose of selling or promoting it. However, in your daily work life, you may spend more effort 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 of this self-imposed exile, they are difficult to link with the sales metrics driving the whole organization.

Make no mistake, the story about the value of your marketing that hooks the CEOs, should be: “Which channel should we best invest in and how much should we invest if we want to achieve a global 10/20/50 percent increase of our sales next month based on our sales forecast?” This channel/metrics connection is crucial in a multitouch world, where your channels and customer interactions 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.

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