While those of us absorbed in the day-to-day of performance marketing are looking for ways to enhance activity and grow sales within the channel, it is important sometimes to step back and think about where performance fits into the bigger picture and what it is that we’re trying to achieve.

All brands have finite marketing budgets and the overarching goal is to spend that budget in the most effective way. There are numerous channels to market and budget needs to be assigned between all of them, from TV to PPC, from print to email.

As commercial director at Performance Horizon, I believe there are two fundamental questions that need to be answered regardless of how the advertising is being carried out:

What impact is the advertising having on introducing customers to the brand and encouraging them to purchase?

What is the value of customers driven by that advertising channel?

Investigating question one initially, in the offline world this is a difficult question to answer. A brand puts an advert in a newspaper and sees an uplift in sales in the days following; which is indicative that it has had an impact. However, in the online world this is a question that we are able to answer as everything is (and should be) trackable and accountable.

Question two is an interesting one. Within offline, brands will decide to advertise in certain newspapers, place billboards in specific locations or appear on different TV channels and radio stations because the demographic of their specific audience consume that media.

If we examine how to measure performance marketing in relation to these two questions, then we come up with the reason that examining data is so important. As we all know, affiliate marketing is not a single marketing channel, but rather a collection of marketing models that all sit under the same umbrella payment mechanism. Therefore there is a need to determine the answers to the two questions above for different affiliate channels, and even for individual affiliates in order to understand how brands should be assigning their marketing budget.

To this end, I have come up with five key pieces of data that all performance marketing practitioners should be monitoring.

Click Path Analysis

Whether looking at this within the performance channel in isolation, or ideally across all online channels, brands should be looking at the role that different affiliates play in the path to sale. Are some affiliates simply coming in at the last minute and dropping cookies when the consumer has already decided to purchase? Perhaps more importantly, are some affiliates involved early in the sales process and are not being rewarded for the activity that they drive? By not rewarding them, brands run the risk of switching off these channels which have been proven as being vital in introducing brands to consumers.

Click to Conversion Times

Your technology provider tracks the time that a click occurs and the time that the subsequent sale happens, and therefore should be able to provide you with the time that has elapsed between the two. A relatively short click to conversion time may lead you to think that the consumer has already made up their mind what to buy before clicking on the affiliate link. Conversely a relatively longer lapse may mean that the affiliate is involved in the introduction of the brand to the consumer. Taking this data in conjunction with the click path data above goes a long way to answering question one above and giving brands a view on the role that each affiliate is playing in the journey to the point of sale.

Rejection Rate

Determining the value of customers will obviously vary by brand with each business having different KPIs to which they work. However, I have tried to be as general as possible in selecting data that is widely available and relevant.

The first thing I think brands should be looking at is rejection rates for different affiliates. Rejected sales cost brands money in the time and resource required to identify and communicate them, and therefore identifying affiliates with abnormally high rejection rates will give the brands not only the opportunity to weed out these partners, but also to identify why this is happening and look at if there is anything that can be done to assist the affiliate. For example, should the affiliate be promoting a different offer or targeting a different type of consumer?

Average Order Value

The most straightforward way of determining the value of a customer is by viewing how much they spend. But how many affiliate managers currently look at AOV by affiliate? It is certainly worth examining the data as in all of the examples I’ve looked at, I’ve seen some startling differences in the average basket amounts driven by different affiliates. Clearly if ‘better’ customers are being driven by certain affiliates, it makes sense to maximise opportunities through those affiliates.

New vs Existing Customers

Again, this will be specific to some brands, but a lot of them will put a greater emphasis on an affiliate sending them a customer who is new to the brand rather than driving an existing customer back. Most technology providers should be able to track this and once again, looking at the difference in rates between affiliates gives brands who consider this important a way of determining the value of different affiliates.

In conclusion, we hear a lot about the importance of data, but in isolation data is useless. It needs to be used to drive valuable insight and I hope I’ve demonstrated five ways to turn data into something that is valuable for performance marketers when looking to optimise their activity.