Big data analytics is what makes intent marketing possible. Big data refers to the process of examining large, complex datasets—which has been made possible by ever-improving computing speeds. Thanks to big data, marketers can observe how consumers interact with their platforms, enabling them to respond to user intent instead of just targeting users based on their demographic profile.
One of the downsides of big data is it gives us infinite ways to measure things. Humans love seeing patterns, and marketers must be cautious not to lead themselves down the wrong path.
So what analytics actually matter when assessing your intent marketing strategy? Let’s break it down:
Identify Actionable Metrics, Avoid Vanity Metrics
Digital marketers must avoid the temptations of ‘vanity metrics.’ In his New York Times bestseller, The Lean Startup, author Eric Ries defines vanity metrics as the numbers that give the rosiest possible picture of a business. These metrics wreak havoc, he says, “because they prey on a weakness of the human mind.”
Growing traffic or revenue might make you feel good, but they don’t necessarily tell you whether your business model is sustainable. If you’re selling ads against traffic, then the number of page visits is important. But if you’re aiming at conversions, your goal should be high-intent traffic, not just any traffic.
Ries recommends identifying actionable metrics that demonstrate cause and effect. When cause and effect are understood, it becomes clear which actions are necessary to replicate the results. Identifying which actionable metrics are best for your business is more challenging than it sounds. According to Forrester, 74% of firms say they want to be data-driven, but only 29% say they’re good at connecting analytics to action.
In the digital marketing world, performance tends to be judged by the “cost-per.” Whether it’s cost per lead (CPL), cost per acquisition (CPA), or cost per click (CPC), the goal is the same: lowering the cost of converting a person into a paying or potential paying customer. To lower your cost-per, you need an actionable metric, and the most effective actionable metric is purchase intent.
To lower your cost-per, you need an actionable metric, and the most effective actionable metric is purchase intent.
Using Analytics to Identify Purchase Intent
Once you’ve identified which customer actions (cause) are high predictors of a purchase (effect), you can then optimize your spending against those actions. How you identify purchase intent should depend on your industry, your brand, and the channels in which you operate. Here are a few places to start:
1. Search terms
Today, more than ever, consumers are beginning their customer journey with search. Take the mortgage lending industry, for example. According to a 2018 Velocify study, borrowers who got a mortgage over the previous 2 years were 3.7 times more likely to find their lender online or through social media than 5 to 10 years ago.
According to Natural Intelligence’s own research, search volume for unbranded search terms, such as “best mortgages,” “best home loans,” and “best home mortgage lenders,” increased 211% between 2010 and 2018. At the same time, searches for branded mortgage keywords like “Bank of America mortgage” and “Chase mortgage” actually fell 62%. Not surprisingly, the average CPC for unbranded mortgage searches has reached $13.55 per keyword, almost seven times higher than for branded mortgage searches.
Online marketers must look to their own conversion rates to find out if the cost of unbranded search terms is worth it. If the CPC for keyword A is twice as high as for keyword B but the conversion rate is 4 times higher, then you now know to target keyword A.
2. Website interaction
Getting a customer to your website is one thing, but how do you learn which actions boost conversions? A good place to start is by segmenting your visitors. For example, you might want to treat first-time visitors, repeat visitors, and buyers as different cohorts. That way, you can see how each group interacts with your website.
Next, find out which website actions signal high intent to purchase. For example, are people more, less, or equally likely to purchase after they’ve subscribed to your newsletter or downloaded a white paper? Compare page visitors and conversion funnels. Is someone more likely to purchase after they’ve viewed one of your products, read about your deals, or browsed the FAQ section? Is live chat with a customer service rep an indicator of purchase intent?
Once you’ve identified high-intent actions, you can then optimize against these actions. Do visits to your “Deals” page show intent? Great, now focus on attracting more people to your Deals page and on offering the types of deals that will cause them to convert.
find out which website actions signal high intent to purchase. (Photo by Igor Miske on Unsplash)
3. Other marketing channels
While website and search are perhaps the most obvious, there are lessons to be learned from every single touchpoint in the customer journey.
Every point at which a customer interacts with your business in some way is a touchpoint. Think about your social media channels. If you market on Facebook, LinkedIn, or Instagram, these are all places you could come into contact with customers. Think offline. If you have physical stores or offices, these are also touchpoints. Every touchpoint presents a chance for you to collect and analyze data on purchase intent. True, collecting offline data requires a bit more effort, but it’s still possible.
Creative thinking is all that’s required to identify actionable metrics for your business.
Target Actions that Signal Intent
Spending on digital marketing now stands at around $100 billion per year, according to UK accountancy firm Moore Stephens. No doubt billions of these dollars are being wasted by companies that haven’t gone to the effort of identifying which actions to target. If you know which customer actions signal intent and which don’t, you can then optimize your spending to focus on the actions that are most valuable.
Capture High-Intent Leads
