Clickers vs Buyers: Using Predictive Marketing for Successful Digital CampaignsJune 13, 2018
Filtering and targeting can be extremely rough when you kick off your digital campaigns by putting a lot of waste into your campaign iterations, but campaigns don’t have to start out this way. Applying direct marketing-style principles can improve online advertising and help marketers paint a better picture of their customer profiles than they can with digital alone.
Marketers often believe, or hope, that they know their audiences well enough to target them without the help of predictive. More often than not, campaign results tell a different story. With AI and predictive targeting, marketers can develop more successful online ad campaigns by targeting a better initial audience than they could have using online filters or a feedback loop.
Have Agencies Lost It?
Today, agencies still have their creative heart, but they’re getting pinched in on both sides by platforms’ more streamlined, self-service approach to media buying, and consultancies specializing in building and executing business strategies with the latest and greatest marketing ad tech.
Tech giants like Facebook and Google have consolidated online traffic on their platforms and become the new audience experts, leaving advertisers, agencies and publishers at the mercy of these tech companies.
When agencies have to rely on Facebook and Google to receive valuable information about consumer audiences, they’ve lost control. True, they played similar games with major publishers and media giants of yesterday, but the power imbalance wasn’t as stark. By banking so heavily on digital early without really knowing what they were doing, agencies turned down a road of lost significance and by losing control of the consumer.
The ongoing issue that agencies face when they turn to platforms with black box approaches to audience targeting and metric tracking is they’re not allowed a true understanding of the inner workings of the platform’s targeting software and have no real idea of who they are targeting.
Agencies who are embracing predictive modeling are discovering it as a way to take back control. It allows direct access to consumers and gives them the power to predict future outcomes and consumer behavior, and find the best customers for their clients, without relying on Facebook to find them for them.
Targeting people digitally typically requires marketers to pick a handful of personas or audiences (using preset filters like: age range, gender, personas, etc.) which they believe will allow them to reach the best audience for their brand.
These filters give marketers a large pool of prospects which they can advertise to and then iterate on in a digital feedback loop. Feedback loops allow marketers to quickly test, learn and adjust campaigns on the fly. The problem is this process can cause marketers to be less concerned that their initial target audience isn’t made up of actual buyers, because they’ve been told that digital iteration is cheap and cost effective and will eventually generate the desired results. Yet digital campaign iteration is often far more costly than expected—enough to cause many marketing campaigns to return negative ROI.
Don’t Kill Your ROI
If you’re calculating your metrics honestly, you’ll often find that running numerous small test campaigns, to find your right audience, significantly increases your ultimate customer of acquisition (CAC) which kills ROI.
Also, using digital-only data for iteration often leads to bad targeting outcomes. Digital campaigns often tend to optimize more towards clickers, regardless of efforts not to. Many campaigns get flooded with clickers that get treated as leads and future marketing dollars are then wasted on them, yet they don’t have the right profile to ever make a purchase.
A lot of people also show ‘false intent’ online, which further distorts digital targeting. Marketers can interpret consumers’ digital signals as an intent to purchase—that the person is in market for one of their products—when in fact they’re not. They may be simply curious, mindlessly window shopping, doing researching, or coveting something out of their reach. Without offline profile data, it’s difficult to identify and suppress people with false intent, which again wastes money.
With false intent, it means that the platform has assumed that someone who shows interest in a product (through their clicks or views) has intent to purchase, when in reality, this person does not have the proper profile, means or capabilities to purchase and is a problem unique to online targeting.
A clicking audience is totally different from your buying audience, and you’ll see your ROI tank when your campaigns investment brings in traffic, clicks, responders, leads and looky-loo’s, but not enough actual purchases.
Clickers vs Buyers
So how do we move from a clicking audience to a buying audience? I’ll give you a hint: it has to do with predictive marketing.
In the past, the upfront cost of predictive targeting was more expensive than online targeting because there wasn’t a lot of automation and it required large teams of data scientists doing manual work and results in long timelines. A single predictive model could take days to weeks to even months.
That’s the brilliance of Reach’s predictive marketing cloud. We’ve created a tool for marketers to use that allows them to do accurate, powerful predictive consumer targeting in minutes.
Our predictive marketing platform automatically wrangles and appends data to create hundreds of predictive models behind the scenes and automatically scores the prospect universe with the model to identify top prospects – no data expertise required.
And it’s not just for direct marketing. The best marketers are taking people-based marketing approach to digital. With tools like Reach Analytics you can get a marketing list of people most likely to become your buyers and then convert them to digital yourself of using a service like LiveRamp to onboard your predictive targeted list targeted to digital IDs for superior digital marketing.
Applying this people-based approach to improve online advertising helps marketers gain a deeper understanding of their brand’s customer profiles and creates a far better initial target audience than could be made using anecdotal online filters or a feedback loop.
Narrow down your universe to the right people before launching campaigns, instead of starting broad and running wasteful test-and-learn iterations. When your universe has been narrowed down to the right populations with offline profile data beforehand, you can then execute better digital campaigns, still optimize quickly for creative and channel using digital feedback loops, and know you’re getting your best results by reaching your best audience of buyers as efficiently as possible.
Digital Marketing Goes Predictive
In the end, predictive targeting will help marketers develop more successful online ad campaigns by targeting a better initial audience, identifying greater insight into what makes target audiences unique, and allowing for better media and channel decisions.
You can get started in minutes with us. Check it out for yourself. Start using ultra-fast predictive marketing to improve your digital targeting. With our easy-to-use cloud software, you can start optimizing your campaigns now to save money and create better ROI.