When surveying the levers that marketers can pull to improve their businesses, there is one lever that keeps squeaking and getting stuck year after year. Unfortunately, that lever is crucial to improving everything else in the marketing machine. We’re speaking, of course, about attribution.
In the age of data, when we’re dealing with hundreds, thousands or even millions of customers, it is crucial to know what’s working and what isn’t before making high-level decisions about our businesses. And, as our data systems evolve, this need for accurate measurement will only grow.
The good news is that marketers are finally recognising the need to evolve their attribution systems. The days of last-click vs first-click are slowly fading into the history of digital advertising, and a new day of custom attribution models is peeking over the horizon.
The insights we found in our latest 'State of Marketing Attribution 2017' study were both encouraging and challenging. As a full-funnel advertising platform working with over 37,000 clients worldwide, we’re always pushing ourselves to use the full strength of our internal data and improve our clients’ bottom lines. But as we’ve found out, and as we’re sure many other marketers have as well, with more complex models come more complex questions. Hopefully the report, and the top 10 tips below, will help answer them for you as it did for us.
1. Start with a clear strategy and set of objectives
Be clear on your objectives from the start, and share them throughout the business, with key performance indicators (KPIs) applied when appropriate. Having a clear set of goals from the outset will help you to decide the nature of the data included in the attribution model, the type of model or models used and the most appropriate technology. Think of the key stakeholders and other teams that need to contribute, and ensure the strategy is communicated to and supported by all developing insightful attribution models.
2. Get internal buy-in for attribution
The impact can be far-reaching, affecting workflows, commissions and bonuses. Failure to get buy-in can lead to a failure to get insights actioned. Senior-level backing for attribution must be sought so that all departments are sold on the benefits, while also being clear on the business goals and methodology. This will help ensure that certain teams don’t become disenfranchised and suddenly question the validity of models when they don’t like the recommended outcomes.
3. Build a strong business case to make the necessary investment
Attribution modelling won’t bring returns without action. A business-wide commitment and sufficient loosening of the company purse strings by the CFO are vital. That said, attribution modelling shouldn’t be seen as a cost centre, but rather as a source of future revenues. In order to fund the necessary investments before, during and after the actual modelling process, a strong business case needs to be built that clearly spells out the return on investment. The business case is likely to focus initially on the savings that a business might make. But the aim should be to increase marketing investment—understanding that larger budgets will deliver more than sufficient payback.
4. Focus on defining the customer journey
This year’s research shows that defining the online customer journey is the most significant barrier to using attribution effectively for brand respondents. Ensure that you take a holistic view of the touchpoints that contribute to the path to purchase. Although they are becoming less linear and funnel-like, it is still possible to build a picture of triggers and typical pathways. A combination of quantitative analysis of existing data and qualitative research— such as focus groups and customer interviews—can help you get closer to a bespoke customer-journey framework that’s tailored to your business.
5. Focus on physical as well as digital touchpoints
It’s an ugly word, but companies need to think ‘phygital’. Attribution needs to encompass traditional marketing and physical-world touchpoints in order to maximise its effectiveness. Every company can benefit from a more connected approach.
6. Make sure that data sets are as clean and accurate as possible
Attribution models are often only as strong as the weakest link in the chain—making it crucial to ensure that data is as consistent and accurate as possible. Data from a growing range of tools and platforms must be cleansed and unified into a consistent format so that it can be plugged into a modelling system. https://www.adroll.com/resources/guides-and-reports/state-of-marketing-attribution-17-uk/viewUnifying data is a clear starting point for developing insightful attribution models.
7. Invest in technology that gives you the required flexibility
There is no shortage of tools on the market to assist in attribution endeavours. However, finding technology that caters to your particular needs can be difficult. Choose a platform that lends itself to continual optimisation—which allows for changes in patterns of behaviour and adjustments to your models—in order to test new hypotheses and continually refine your approach.
8. Try different models that align with your business goals
Algorithmic models for attribution rely on rich, solid data sets and tend to be used by those further up on the data maturity scale. But there’s no reason why companies at all levels can’t aim towards this. Try to remove biases through last-click/first-click models and see which channels really drive impact. Experimenting with different attribution models and methods allows you to determine what works best for your data and which processes will be most effective.
9. Use a test-and-learn approach
Companies can benefit from an ‘agile’ approach that is rooted in a commitment to test and learn. Consolidate your data first to understand which channels deliver results aligned with assigned budgets. After that, move into modelling the data, making small changes each time to move closer to your goal. Testing needs to occur before confidence can be put into any attribution model, which is where many companies can stumble with the implementation process. Testing against a forecasting tool can instil confidence that the correct balance is being achieved.
10. Focus on recruitment and training
When hiring the right people, companies must understand that successful marketing attribution is a combination of science and art. Recruiting the right mix of analytics skills, broader commercial awareness and softer skills helps facilitate cooperation across the organisation. It’s equally important that existing staff are equipped with the right skill sets and knowledge. Vendors and agencies can support this, but the training regime ultimately needs to be controlled in-house to ensure that the tail isn’t wagging the dog. Employees need to feel empowered when it comes to handling data, which, in turn, increases the effectiveness of attribution.
From the uptake of attribution modelling and use of specific methods, to attribution system flexibility, multichannel attribution and confidence in agency impartiality - check out AdRoll's State of Marketing Attribution 2017' study here.