The affiliate channel has been built around Cost per Action and Cost per Click as the chief and fundamental forms of measuring and attributing a programme’s success, but in 2018, do these still hold the line as the most effective and representative metrics?
According to Impact’s co-founder Todd Crawford, while they effective in certain scenarios, the channel’s evolution, diversity, and crucially its continued adoption among advertisers, hinges on a move away from “traditional” metrics to some of those less considered, but equally valuable.
First off, Todd, where do you think we’re at currently - as a global industry - when it comes to measuring the performance of affiliate marketing campaigns?
Todd Crawford: I don’t think performance marketing is alone when it comes to this question; I think all marketers are struggling to get data that is accurate and meaningful to their business. They’re looking at the same old data all the time and not necessarily progressing. A lot of marketers - including those in performance - are just sticking with what they know and not really understanding that there might be something better out there; something more valuable.
Have we arrived at a point where we should be considering a move away from “traditional” metrics, such as CPC and CPA, and if so, why is that?
TC: I think CPA and CPC are fine metrics, and there are other traditional metrics like Conversion Rate [CR] and revenue that have their place, but there are better ones that together with these legacy metrics will provide a better perspective on the true value of the channel and the individual partners within the channel.
There’s no denying that CR is a ‘metric’, but what does it really do for you as a brand? What does a higher or lower or average CR really show? On the other hand, revenue is a more important measurement for a channel owner that is potentially measured on revenues, but revenue alone doesn’t really help me understand enough.
Now that data has progressed we should look to new metrics, which in terms of what can be tracked and analysed will provide more insight into what’s already being measured and help marketers understand where the channel is stronger or weaker.
So where should we be focusing in order to identify the true success of affiliate campaigns?
TC: It’s going to be different for every brand, but you have to ask yourself; what does your brand value most besides revenue? A common one is new customers; of course, we want lots of revenue for existing customers but that’s probably not a very strong business model. Instead, we need to constantly be acquiring new customers.
If you understand the revenue at the partner level, and can then break it out by how much was from new versus returning customers, it would give you a better perspective on each partner’s contribution to your business objective of acquiring new customers.
Within Impact, can you point to any specific brand examples of this in practice already?
TC: It’s part of our Insights reporting suite and again, part of it depends on the brand; what metrics they want to supplement to Impact. By combining advertiser KPIs with the data Impact captures, it becomes even more valuable to the brand.
As affiliate managers, we’re typically looking at a very siloed view of our data; in many cases, networks can only show you the winning affiliate - they can’t tell you the other affiliates that were involved but didn’t win, much less the other channels that were also involved in the customer journey. Without this perspective, it makes it very difficult to understand how your partners are contributing to revenues being rewarded to other partners or paid media.
New-to-file customers are always going to be important, but if your CMO calls a marketing team meeting and says that ‘this year our number one goal is new customers’, then that insight has a far greater meaning, and if you don’t have that granular insight you’re going to be struggling to execute on that goal.
Could you give some examples of how this would be quantifiable as metrics and how they could be rewarded?
TC: Something you hear a lot about in this industry are the challenges around last-click crediting. There are a large set of partners out there that are very good at working with last click, because of where the consumer thinks about them in consideration when purchasing - such as voucher and cashback sites, for example, which occur near the checkout - but there are often other partners higher up the stream. So, what I want to understand is not just revenue when the affiliate was credited with the sale, but what other revenue did they participate in and were not credited?
I think one of the most important data points is analysing participated versus credited revenues. For example, at the end of a given month a partner was credited - and earned a commission - with £100,000 of revenue, but there’s another £100,000 that they participated in but weren’t last click - so they contributed in £200,000 of revenues. Taking this a step further, of the £100,000 they were credited with, what percent were they the only touch point in the consumer journey? If the data shows that 50% of that £100,000 was unique to that partner, then that means they are the only source of £50,000 in revenue - again, another valuable perspective on the same old revenue number that demonstrates incremental revenues.
In other words, if a million pounds a year of revenue is coming from a partner that I can’t get from any other partners or any other paid media, then that’s a valuable partner. I would think of that revenue differently than if I didn’t have that perspective on those revenues.
How could the proliferation of new metrics such as these impact and change the perception of the workings of the wider affiliate marketing ecosystem?
TC: From a marketer’s standpoint if I managed the channel; the richer the data, the more value I can associate with the channel and individual partners, the easier it is for me to champion the channel internally and explain why affiliate is so important to our brand by demonstrating the value it’s bringing.
In a worst case scenario, when people question the value of the channel or specific partners, I can defend the channel more intelligently. If I’m blind to all these data points, or my CMO is pulling some analytics data that I don’t necessarily believe is accurately reflecting my channel, I’m in kind of a bad position.
This approach is the best thing that can happen for the longevity of the industry, because we are seeing influencers coming into the channel; we are seeing small and medium business development deals being put into the channel; we are seeing brands starting to really want to expand what is performance marketing beyond the narrow affiliate market, and this is such good news for our industry. However, we need the tools and the data to make those kinds of partnerships workand accurately measure and reward them.
What are some of the challenges we face when implementing these metrics?
TC: The first thing is the marketer needs to understand what will they find as the most valuable, outside of just revenue. Maybe you don’t know, so work with your vendor to find out what additional metrics are even available. We talk to clients all time that are excited and surprised that we’re able to capture and report on data that they aren’t used to looking at. Once they see that data and start using it, they don’t ever want to go back to not having it.
You’re trying to paint the richest picture in understanding the channel and individual partners in ways that other channel managers may not have access to. I always try to advocate that the people in our industry should be the smartest people in the room and on the team - I want them to understand data and elevate their entire organisation. If the performance channel is the first to have these metrics and the CMO or director realises how powerful they can be and then wants to implement them across all channels, that’s really a positive thing.
What kind of advice would you give to an advertiser who wanted to convince their network to move away from last click?
TC: Last click works if you have a lot of data that helps you understand it. If you have two partners and one is highly rewarded on last click and one participates a lot and rarely wins on last click, then I think it’s fair - based on all the data, to change how you work with that one affected partner. So now that I understand the problem for this one partner I can fix it; I can do tenancy buys, spot bonuses, or I can increase their commission so that the times that they do win compensates them for the times that they participate and don’t win. I could also work out some kind of split, so only when this affiliate wins, and this higher funnel affiliate is involved, I want a split. I’m not trying to create a commission-splitting scheme for the entire channel, I’m trying to be very strategic and identify whether I have a problem, who’s affected by it and under what conditions and then determine what are the best options to solve it.
I’m an advocate of the easiest way to solve it rather than the most complex. Splitting commission is probably one of the more complex as there’s a lot of “if-then” formulas that you have to consider whereas if I just say to the higher-funnel partner; “I’ve noticed you’re participating in a lot of conversions, your content is amazing, I want to pay you £100 bonus every week or every month because you’re not always winning as much as you should”, you’d be surprised how excited you can make that partner. No other advertiser will have ever reached out to them and told them that and rewarded them for it, so communication is key too. If you’re making these changes, you need to reach out and let them know. Conversely, if you’re splitting commissions or pulling commissions, you need to let them know why with the data to support your decision.
Do you think this shift is going to take over the industry?
TC: You hear all the time that people are trying to figure this out and overcome the flaws of last click, acknowledging partners up the funnel that are adding value. The shortcuts or first answer is not always going to be the best; people are trying out things, but to me, data comes first. If you can clearly see the problem then you can try and fix it and then you have the same data available to measure it afterwards to see if you got the desired results. That to me is key to understanding if you’re fixing the problem or just treading water.