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Five uses of data to fuel insights

Five uses of data to fuel insights


We live in an age of data overload. As someone whose team spends much of their working day deciding the most insightful ways of extracting and packaging that data to answer the growing number of advertiser, agency and publisher enquiries, so it’s vital work out what the end goal of the analysis is.

This is the critical point and one that can quite easily be relatively straightforward. Invariably the devil is in the detail and often by trying to address those bigger picture questions, new layers and avenues of insight emerge.

For the purposes of this article I thought it would be useful to look at some of the common questions and emerging trends that data will play a central role in. I can’t obviously do any of them justice in a few hundred words but can hopefully set the scene on some areas that we are either tackling now or will have to in the future. It’s almost more about solidifying affiliate marketing at the heart of an advertiser’s campaign rather than driving revenues ever upwards. However If we can do the former then hopefully the latter will be significantly easier to achieve.

1. Incrementality

Is it a word or isn’t it? Incrementality has become such an everyday part of the affiliate landscape that it doesn’t seem to matter anymore. There’s no doubt this is the big one. Barely a day goes past without a client request or general enquiry about how we prove the value of the channel.

Let’s be clear, this typically centres itself on the growth in incentivised traffic and as such data holds the key. Assess new customer numbers, closeness to sale and (often overlooked) the lag time between penultimate and ultimate click prior to sale. Lifetime value, frequency of purchase, basket size and products purchased all help to shape the customer being driven by your affiliates.

This data doesn’t exist alone. Pull in publisher, client and network information and pivot it in Excel. You may be surprised by your findings. We’ve long said as a network, for example, that affiliate sales are typically single interaction – as high as 90% in some cases, so from a channel cannibalisation point of view there’s little to argue about.

If you’d like to read more about measuring incrementality you can receive our February 2012 white paper by emailing me.

2. Segmenting

This rather neatly moves me to the next point, one that I’ve spent years trying to mitigate yet still seems to form much of an advertiser’s approach to managing their campaign: affiliate segmentation.

In many ways we only have ourselves to blame. From five years ago when we would talk about how affiliates as a whole performed we then moved to talking about how different types of affiliates perform. This was a necessary development as affiliate marketing represents a diverse and disparate group of marketing techniques. However we stopped there. So when we talk about having a cashback or loyalty and reward policy for example we trample over all the data that actually shows they clearly attract different customers. Take one recent example. When we accessed a client’s data for new customers being driven by their top 15 affiliates, we found one loyalty site boasted an average order value three times that of a competitor affiliate in the same category. It doesn’t take a genius to work out they’re clearly attracting a different customer, so why treat both the same? Understand the difference and it might transform your relationship with that affiliate.

3. Join up the data

An increasing challenge and one that isn’t difficult if you can secure buy-in from multiple parties. Affiliate marketing doesn’t exist in a vacuum and too often we’ll try and understand the channel in isolation. When affiliate marketing can account for less than ten per cent of sales this doesn’t make sense. Reference the above metrics but weave affiliate within the data. Again, do it by individual affiliate as channel insight alone adds little to equation.

My team at Affiliate Window has carried out this insight for a number of advertisers and the findings always throw up some interesting conclusions that impact business decisions.

4. Dig deeper

Evolving my earlier point about looking at affiliate data on a granular basis, why not go one layer deeper? Major UK affiliates are multi-channel now, encompassing traditional desktop activity with tenancy, push emails, mobile sites, apps, online to offline tracking and much more. We’re at a crossroads now where we need to understand what that looks at collectively but also individually.

Do consumers act differently according to the promotional activity drives? This is a new challenge for all us but there’s no doubt the data will be fascinating.

5. The new age of mobile

With handset Internet activity booming so we need to understand the mechanics and how consumers are interacting with them. Take email affiliates. Countless surveys show people are abandoning desktop to access their emails; what are affiliates doing to capitalise on this? Also what products are they purchasing? Group buying for example does well on mobile for us and one email marketer is driving four times as many sales as our network average through handsets.

This is largely happening relatively passively at the moment with few dedicated mobile marketing pushes. This will change and 2013 is likely to see the dawn of a much more concerted mobile effort within the channel.

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Kevin Edwards

Kevin Edwards

Kevin Edwards has over 15 years experience working for affiliate networks.

Working as global client strategy director for Awin, Kevin is responsible for empowering the company’s employees and clients with the right data and insights to make the most informed decisions about their campaigns. He also takes an active role in creating best practice standards and self-regulation. Kevin was previously Chair of the Affiliate Marketing Council in the UK and continues to play an active role in the IAB’s Legislation and Standards’ Committee.


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