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In a recent survey, 76% of marketers said their biggest challenge in influencer marketing is determining campaign return on investment (ROI). I know from having worked on over 150 such programs in just the last few years that there is no perfect system that works across industry sectors. But you very much can build programs that allow you to see and measure real results.
Before we dive in, you should consider the many variables impacting what methodology is the best fit for you. This includes how you sell (direct to consumer, through retailers, through channel partners, as an “ingredient” in another product, etc.) and what you sell (expensive purchase or impulse buy, purchased weekly or every few years). This affects how quickly you can reasonably expect to see an impact from any short-lived marketing campaign.
The other factor to consider is the data your company already collects and how you measure returns on other marketing investments. Attribution is tricky, and it’s very likely that your brand has considered similar questions to measure the impact of TV or print advertising or even digital efforts. Often the best way to go is to adapt those methodologies for influencer marketing so that the strengths and weaknesses of the attribution model are applied evenly across tactics.
With that said, here are five influencer marketing metrics our agency likes to use that you probably don’t know about:
1. Estimated Ad Recall Rate
What It Is: A metric provided by Facebook and Instagram for when a company wants to measure brand awareness. According to Facebook, it’s “an estimate of the number of additional people who may remember seeing your ads, if asked, within 2 days.”
Pros: Since it’s an estimate based on machine learning from larger Facebook research efforts, you can get a tangible number without a tremendously large advertising commitment. We’ve found that 6% is a good benchmark to measure performance against. You can also measure against the ad recall rate of your brand social posts to see which are “sticking” better.
Cons: It’s not very flexible. For example, Facebook asks an exposed control audience if they remember seeing ads for a particular brand. But the questions in these surveys are templated and can’t be changed to fit each brand’s needs. You will also only be able to apply this to boosted influencer posts, so you won’t get metrics for the organic reach the influencers drive.
2. Sales Lift Analysis
What It Is: A correlation analysis run by an analytics team that maps campaign data (such as delivery of content views) to sales data to determine whether the campaign impacted sales in the target market.
Pros: Since this is typically done using data that teams already have, there is no incremental cost besides the labor of the data analyst. Ideally, it compares against both a pre-campaign period and a relevant benchmark period to try to strip out other contributing factors.
Cons: Seasonality, natural consumer buying cycles and other promotions (pricing changes, retail placement changes, other marketing support) can be difficult to isolate. Similarly, aggressive competitor marketing efforts can suppress sales during either the campaign period or the benchmark period. It takes some effort to isolate a clean benchmark.
3. Conversion Analysis
What It Is: For e-commerce brands, an analysis of the conversions (purchases, registrations) driven by audiences reached with influencer content from the campaign.
Pros: Using Facebook’s pixel, a brand or retailer can track exposure to the content and then see which of the exposed audiences converted, even if they do not click the link. This can give you real sales values from people who see the influencer content.
Cons: Facebook will take 100% credit for any sales among exposed audiences, even if they were impacted by other marketing. This typically leads to numbers that are over-reported relative to what the brand sees with direct attribution. Ideally, an attribution formula is agreed to in advance for both “viewed then converted” and “clicked then converted” actions. We have seen a majority of sales for some clients coming within 24 hours of exposure but from people who never clicked, so last-click attribution is under-counting.
4. Search And Direct Traffic Lift
What It Is: For that same client where we saw the majority of purchases coming from people who never clicked, we also saw big increases in direct web traffic and organic search traffic. Given that, looking for and analyzing any similar such lifts creates a more complete picture of the impact of influencer.
Pros: Assuming a brand has good data on its normal levels of organic and direct web traffic, and assuming these spikes correlate with the beginning and end of influencer programs, this is an excellent way to get a more complete picture of the outcome of an influencer program. We’ve learned that many people who are interested do not click links. They move over to a new tab and type the brand URL or search for the brand on Google.
Cons: This will not provide a complete picture of a campaign’s results. But adding it into another measurement technique can surface an important new brand benefit.
5. Content Effectiveness Study
What It Is: A custom survey designed to measure the likely impact the influencer content had on key awareness and messaging objectives. Volunteers are recruited to review content in a simulated social network setting designed to replicate how they’d see content online. This option requires brands to work with a third-party company that specializes in this work.
Pros: Because this is a custom survey, it can be built to measure the content impact on campaign-relevant objectives. This is done via a survey that takes place in a simulation of the social channels on which the content was originally served.
Cons: Expect this to be at least an additional $30,000 investment and take about six weeks. It also utilizes a proxy sample audience to mirror the target population, not the actual audiences exposed in the wild.
Measuring influencer marketing isn’t easy, but it is achievable. As investments in the space increase, our ability to measure results must also grow.
