Second in a five-part series on social media marketing for startups. The first part explores why social media advertising matters.
You’ve heard a lot of talk over the past few years about performance marketing, but what does it really mean? Sometimes you’ll hear it presented as the opposite of brand marketing or as the “math” part of marketing.
For me, it’s bigger picture than that. While it’s true that performance marketing is rooted in data and performance objectives are different from brand objectives, I think there’s a continual improvement aspect that’s key.
Performance marketing is a discipline that uses data feedback from digital conversions to improve advertising efficiency over time. This can be best thought of as a five-part loop: You define an objective and formulate a hypothesis, design and run campaigns, analyze data compared to the original objective and convert data into insights to develop new objectives and campaigns.
Let’s look at each of these stages individually and focus on what makes them critical for performance marketing.
Everything starts with: What am I trying to do, and how might I measure it?
Once the objective is set, the data science aligns with this goal and tries to optimize the campaigns to maximize results specifically for this objective.
It’s critical to align your ad and business objectives to ensure the conversions you measure and scrutinize are a correct representation of the conversions that lead to your business results.
Example: A Shopify merchant sells shoes and defines their goal as selling as many shoes at the lowest customer acquisition cost possible. They optimize for sales conversions and track the volume of sales and marketing cost per order.
Example: An online insurance company wants policy leads and considers a conversion as someone who completes their online form and submits their personal information. The company optimizes for leads and measures both the cost to generate a lead and the quality of the leads generated.
Example: A mobile gaming app wants to increase their number of users. They optimize for mobile app installs and measure both the cost to generate an install and the total number of app installs. The ad’s “call to action” goes directly to the app store and tracks successful installs as conversions.
This deserves its own chapter, but suffice it to say that campaign design is a critical step in the performance marketing cycle.
I think about the often quoted but rarely executed adage of delivering “the right message to the right people at the right time.” This is the stage at which that effort comes together.
The right people
This is ad targeting. The goal is to minimize waste and maximize efficiency by targeting a pool that’s big enough to achieve your goals but small enough to minimize spending waste. You need multiple campaigns directed at multiple target audiences to succeed.
The right message
When you run parallel campaigns targeting different groups with different messaging, you’re able to deliver tailored messages to each group at scale. If your target audiences can be satisfied with the same messaging, then you should revisit your buyer personas and use cases. The better thought out your buyer personas are, the better you can ensure your messaging targets their specific needs in the way they want to receive it. That’s why when all else fails, I think of use cases instead of buyer personas, as it’s easier to create bespoke messaging for a use case than a market segment.
The right time
Here’s where things get three-dimensional. In addition to thinking about targeting and messaging (also talked about as product–market fit), we also need to sequence the messages based on the understanding that consumers are constantly entering and exiting the journey and need different help at different times. Some of our audience have never heard of us, while some are long-time fans or past customers.
By thinking in funnels, we’re able to design a campaign that walks users through a well-sequenced series of messaging, taking them from stranger to customer in sequence. By creating a measurable set of escalating conversions based on common sense, you can start to automate your customer journey for maximum efficiency.
As campaigns run, they spit out tons of very valuable data. Even when campaigns aren’t working to expectation, you can still be learning a lot if you pay attention to the relative differences in the results. Over time, and if the campaigns are designed correctly, this data begins to paint a picture (to an experienced eye) of how to efficiently spend your overall budget.
The key learning here—and don’t shrug it off if it seems obvious—is that to test something, you have to hold all the variables constant except the one you’re testing. If you can’t get to the point where you know what changes drove which results, you will be forced to guess and potentially come to the wrong conclusion. That’s why campaign design is so critical.
Most brands don’t have data scientists on-board, so the key is to analyze the signals or patterns that emerge, based on your past experiences, that show what’s really happening. Over time, you’ll see the same patterns arise, making it easier to determine the reason a campaign is underperforming, or which campaigns to scale.
Ask your team: “So what did we learn, and what are we going to do next time to improve our advertising efficiency?”
The underlying assumption in that statement is that you have campaigns that are designed for an always-on workload and provide the foundation to improve into the future, based on learnings from past applicable campaigns.
When brands think of their advertising year in terms of separate campaigns, they don’t set themselves up for performance marketing, because each campaign launches and ends, and a new one is imagined. The problem is that the new campaign is likely so different from the past ones that the learnings are not applicable.
This is old-world marketing. Digital allows us to build advertising engines we can improve month after month, compounding small improvements into large annual wins.
That does not mean you have to show the same ad all year. It means you need a stable foundation upon which to introduce new ad campaigns based on the learnings from past applicable ones.
Taking the learnings from a past applicable campaign and using them to make your next one better is at the heart of performance marketing. The more often you can complete this cycle, the more you will improve your campaigns and your marketing efficiency will increase.