The Data Challenge | Why Bigger Isn’t Necessarily Better

The Data Challenge | Why Bigger Isn’t Necessarily Better

Words: Kevin Edwards, Founder and Director of the APMA
We are delighted to launch our NEW Contributor Series, kicking off with this insightful article from Kevin Edwards, Founder and Director of the APMA. This month, Kevin shares his ideas on information – the lifeblood of the affiliate business…
The Impact of Data 
If you’re employed within the affiliate channel, you’re in all probability surrounded by information. It’s the lifeblood that programs by means of each associates program’s veins and the DNA of the business. 
The three key features of a normal associates program: monitoring, reporting and funds, are premised on correct information assortment and apportionment. Do these nicely and the remaining is ornament.
That identical core precept holds at this time. However, within the interim, the channel has grown in sophistication. Programs have diversified, hundreds of recent companies have flocked to it and conservative estimates counsel it’s liable for greater than £20bn of the UK’s retail gross sales. Beyond the tens of millions of gross sales, take into account the billions of clicks and impressions and the numerous particular person rows of knowledge that might be tracked – within the time it takes you to learn this.
While nothing in internet affiliate marketing is infinite, making sense of those seemingly limitless interactions which are taking place between hundreds of companies every day, stays one in every of our greatest challenges.
Is Knowledge Power?
In our want to get beneath the pores and skin of affiliate programmes and perceive their true worth, we’re additionally asking manufacturers and publishers to go again significantly extra information factors, layering our quantitative information with extra qualitative insights.
Let’s take the instance of a web based journey enterprise that desires to know which of its associates are driving their optimum clients. They can monitor keep date, location, lodge ranking, automotive rent and breakfast bookings. This information could be aggregated, filtered and apportioned to people or teams of associates offering deeper insights and, within the age of AI, theoretically generate suggestions for us.
But in striving to be taught extra, we threat changing into ensnared by the factor we thought would liberate us. 
I keep in mind quite a few, enthusiastic conversations with retail affiliate managers who had been excited in regards to the new boundaries that information assortment and evaluation would break, giving them the sting and forging new methods. When offered with these new studies, nonetheless, they had been unclear about the right way to create actions from it and assimilate it inside their enterprise as common. Consequently, the studies fell out of favour till they had been deserted altogether. Back to the drafting board.
My notion was that the information – and subsequently the studies – didn’t simply slot into the day-to-day operating of programmes and subsequently weren’t embedded inside companies. They had been highly effective datasets however not essentially outcome-focused. Without this structural strategy, the studies struggled to place themselves as one thing apart from a ‘good to have’. 
What Does This Mean for Affiliate Programs?
Fundamentally an organization has to resolve what it’s attempting to attain with its associates program. For new entrants that may sometimes be, nicely, gross sales. But affiliate packages are all the time on. This means, over time as packages mature and alter in nature, new objectives might be outlined: focused clients, new segments, perhaps a deal with retention.
Having a transparent imaginative and prescient from the outset ought to result in a full understanding of what information factors might help ship insights. The vital step is how these insights are then was actions. It’s one factor to know {that a} specific affiliate is nice at producing high-value gross sales, however what steps should be taken to encourage them to drive extra of these clients? 
That’s the place information platforms need to be interoperable and algorithmic. This is very true for packages with lots of, or certainly hundreds, of energetic publishers. Having a high quality rating, for instance, or suggestions which are baked into reporting programs based mostly on firm objectives, will assist affiliate managers make faster and extra knowledgeable selections.
This will sometimes be manifested in the right way to pay optimum commissions. In different phrases, manufacturers might be extra keen to offer larger charges to these publishers who’re driving the fitting varieties of clients for them. Of course, there’s a counter to that and it might result in tough discussions with different associates who’re providing much less worth. But, we should always all be striving for higher and highlighting what beauty like permits others to enhance.
How Far Are We From Such a Vision? 
It feels to me that datasets are much less fragmented now than they was once. Having these ‘discuss’ to one another ought to produce higher readability and be excessive on the precedence record of any tech supplier. However, there may be nonetheless a reticence throughout the affiliate business to attach writer, advertiser and community information collectively to kind a single buyer view.
There’s additionally information minimisation to think about. This is the idea, baked into GDPR, that corporations ought to solely accumulate the information they should do their jobs. Simply throwing the kitchen sink on the information drawback on the belief that in some unspecified time in the future somebody would possibly need to use it must be frowned on. This is a cultural shift that corporations ought to have made by now.
We shouldn’t be accumulating information simply because we are able to and platforms allow it. Clarity of function mixed with a laser deal with the information wanted to attain these goals must be the foundations of any associates program.
I’m inspired by how reporting platforms at the moment are adapting to provide extra algorithmic outcomes based mostly on these objectives. And with machine studying utilized to complicated datasets maybe we’re beginning to see the bridging of conventional reporting and the context it must drive totally different outcomes. 
Key Action Points:

Define precisely what it’s that you just wish to obtain together with your associates program. 
Redefine these objectives, as and when crucial, as this system grows.
Ensure that information platforms are interoperable and algorithmic.
Remember to retain a readability of function.

Listen to our current podcast with Kevin, the place he discusses the work of the APMA, business challenges which are being solved, and the one phrase that we should always all be fascinated about as we head into 2024. Listen in right here. 
Would you wish to be featured as a Guest Contributor with Affiverse?We’re all the time excited about receiving information and views to share on our website. Please contact [email protected]
Are you registered for VIP entry to AMPLIFY 2024?Always be studying…. There’s nonetheless time to safe your seat at subsequent yr’s unmissable digital studying occasion. VIP tickets allow you to hitch us for the live-stream periods on March 19 and 20. Your VIP ticket additionally offers you entry to all the content material after the occasion to look at at a time to go well with you.
Get your ticket right here

You May Also Like

About the Author: Amanda