Targeting relevant customers is an ongoing challenge in advertising. Some people are looking for products like yours and others aren’t, and if you’re serving the wrong kind of ads to the latter group, you’re throwing away money. These mix-ups may seem inevitable – after all, how much can you really know about the vast numbers of internet users your ads are reaching – especially when you’re using generic groupings such as age or gender to target them? But the fact is, there are actually telltale signs about what people want and the best way to interact with them – and these insights are trapped in your own systems, waiting to be connected and used.
Relevance rates are low for obvious reasons
At the moment, your message is likely only resonating with a fraction of people receiving your ads. Accenture recently asked CMOs how many of the recipients of their marketing messages are actively ready to buy the products in question. The numbers were low, even for the top methods. Online ads are reaching an 18 percent relevant audience, with mobile campaigns and paid search performing even worse. This means there’s plenty of room to make changes, and it starts with improving audience targeting.
Look-alike targeting brings more relevance – when used right
One way to try and boost the relevance of your online campaigns and narrow down your audience is through look-alike targeting. General details of your current customers’ activities may point to larger trends, and the types of behaviors that make someone into a likely buyer of your particular products. As Business 2 Community contributor Tamara Weintraub specified, this takes the theories behind retargeting – showing ads to people who have visited your site – and expands the net to include those who leave a similar online trail.
Of course, look-alike targeting is only as good as the data that goes into it. A failure to gather enough information or put it together into coherent buyer profiles could hurt your ability to reach new consumers. The point of such a program is to reach out to a whole new group of potential customers, using your current base as a template that will help you and these fresh buyers find one another. As Weintraub pointed out, you should be retargeting to keep existing audiences loyal and using look-alike targeting to swell your number of clients.
But where does the data come from to build these in-depth models? You may be surprised about how much relevant information you already have. You just need to connect it.
You already have the data – or at least, access to it
Your websites are great data collection tools. Everyone who visits your online presence, either via a desktop or a mobile device, is leaving a trail. If you can follow the information trail left by their clicks – what they seek out, how long they stay, how they found the site – you have a valuable picture of what a visitor looks like and wants.
Combining and comparing the behavior displayed across channels with existing customer data stored in other systems can deliver a nuanced picture of the different segments that can be revealed within your audience. Better segmentation distinguishes between when someone who is a valuable customer and you’d want to target more of, and a casual one who may not be worth spending ad dollars on.
For example, a leading telecom customer built a data hub with CRM data from three different internal CRM sources (the CRM database of the Internet customer base, the CRM database of TV database and the CRM database of the voice database). The BlueConic ID and the Double-Click data are combined for each individual are sent to the data hub. Based on the BlueConic ID, the segmented CRM data is pushed back to the websites where the audiences are served with very segmented messages.
Better click-through rate means money well spent
Creating good customer profiles with unified data can help you save money in very few steps. Once you know more about your audience, it’s easier to control who sees your display ads, and this kind of relevance can provide an instant boost to click-through rate. When you’re paying for exposure based on how many people will encounter the ads, it makes sense to try every approach to making sure a big segment of the audience is actually interested in what you’re selling.