The ‘must-knows’ on how to achieve a data-driven attribution model

The ‘must-knows’ on how to achieve a data-driven attribution model

With the increasing complexity of the customer journey, traditional single-touch attribution models are no longer sufficient. Customers now carry out multi-channel, multi-device journeys, and companies are having to keep up with these ever changing life-cycles.

In line with this is the increased need for businesses to focus on attribution, to ensure that they are properly measuring the relative impact across these different channels.

During a recent webinar on mastering the art of data-driven attribution, held by ClickZ in partnership with Fospha, close to 100 marketers were polled on their use of various attribution models.

49% of respondents were found to still be using a last-click approach to attribution, while the next most popular model was first click – represented by 13% of the audience. These stats suggest that a large proportion of companies are still using rudimental, early models of attribution that may not provide the most accurate measure of which channels contribute to which conversions.

In the previous two installments of this series, we looked at the challenges of attributing ROI to various channels and the top seven barriers to successful attribution. In this article, I’ll look at the ‘must-knows’ on how to achieve a data-driven attribution model and tailor it to the needs of your brand.

Content produced in association with Fospha.

mca graph.png

Marketing-channel attribution (MCA) is becoming increasingly prominent, with the customer journey now ‘nonline’: non-linear, online and offline and over multiple devices. This complex, multi-touch journey means there has never been a better time to take advantage of this rapidly-evolving marketing area.

The problem is that too many marketers either don’t know how to achieve data-driven attribution, or are de-prioritising it as a project for which they won’t be able to realise any revenue benefit ‘in-year’. As a result, most are are settling with easily available, ‘off the shelf’ models.

But with cost of acquisition rising, there is no better reason to focus on getting a data-driven model in place.

Build incrementally towards attribution

Basic attribution is better than no attribution, so marketers should start simple and aim to build sophistication incrementally.

An important point highlighted during the Mastering the Art of Data-Driven Attribution webinar, in light of the poll findings, was that models like last and first-click attribution are certainly better than nothing.

Making sure you have an attribution model in place is the first step in effective data-driven marketing, and from here businesses can make incremental changes to move into a more sophisticated model.

Step two: Using a Customer Data Platform

The next step towards integrating data in a manner that is conducive to sophisticated attribution is a Customer Data Platform (CDP). Gartner’s defines a CDP as:

“An integrated customer database managed by marketers that unifies a company’s customer data from marketing, sales and service channels” to enable them to drive conversion, increase lifetime value and manage costs vs revenue.

To build a tailor-made attribution model that is a perfect fit for their brand, customers and priorities, marketers need to use a Customer Data Platform as their attribution source, to gain a holistic view of how customers are progressing through their journey.

Models such as last-click fall short as they fail to accurately attribute value to marketing channels. For instance, if all the credit is placed on either the first or last click, there is no understanding of how other journey touchpoints have contributed to brand awareness or conversions.

This lack of visibility results in a limited understanding of multi-touch, cross-channel behavior, which in turn hinders brands from unlocking the full potential of their marketing spend. A CDP breaks down data silos to unify data from various channels and devices and is increasingly being recognized as the go-to standard for an effective data management database.

Using a custom attribution model provides flexibility, allowing marketers to apply personalized rules that are tailored to your business goals and strategies. If the resources to create this do not exist in-house, finding a company that can provide this service will prove incredibly valuable.

Attribution is not a one-time activity

The final point to remember is that as your business grows, your attribution model has to evolve alongside it.

This approach allows your business to obtain a model that evolves as your data improves, so you don’t end up with a model that you don’t understand, or which has failed to keep up with your business.

A data-driven approach also enables predictive modelling, allowing your brand to experiment quickly without real life impacts.

Although marketing-channel attribution may seem complicated, especially if your business lacks advanced analytics, the impact of not getting it right is too large to ignore. Controlling cost is becoming more challenging, and old attribution models will continuously undervalue the impact of many of your marketing channels.

There has never been a better time to start adopting data-driven attribution models.

If you’re interested in learning about how to use a Customer Data Platform for personalization, don’t miss our upcoming webinar, ‘The Personalization Masterclass: Maximising Your Customer Data‘ in partnership with Fospha.


This concludes our series on using data-driven attribution in your marketing campaigns. Read the previous installments in the series:

Content produced in association with Fospha. Click here to read our collaborative content guidelines. Views and opinions expressed in this article do not necessarily reflect those of ClickZ.


via ClickZ

June 19, 2017 at 02:08PM


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