Using Your Data to Supercharge Your Marketing: Advertising

Data has been called the most valuable resource on the planet. The benefits of utilizing your data for a multitude of purposes are obvious, which is why we strongly recommend harnessing all of your customer and prospect data using a Customer Relationship Management system.

Using your data can supercharge your marketing; for making key marketing decisions about products and services, advertising your business, and developing relationships with your customers. Part 1 of this two article series will focus on digital advertising. Part 2 will go into the relationship side of using data: email marketing and marketing automation.

Frequency tends to be the enemy of digital advertising. Does your budget have the ability to reach your target audience enough times during a campaign that your message will resonate and be remembered by your target when it comes time for them to make a purchase decision? Brand recall can be directly correlated to the frequency, or number of times your message is seen by your audience. Frequency can be very hard to attain in the digital realm where there may literally be millions of ads “spots” available, but you can only afford thousands.

Using your data can help you narrow who sees your ads and make your advertising more efficient.

Before you start using your data, make sure it is as accurate as possible. If you are dealing with thousands of records, chances are some of the email or physical addresses may be inaccurate or missing. There are companies (including Digiarks) that can do a data append to take your data and attempt to fill in what is missing or known to be incorrect.

Beware though - nothing replaces accurate data collection from the start. The best these services can usually do is obtain 15-25% of the missing/incorrect physical and email addresses. That still could be thousands of pieces of data added into your database. Two thousand additional email addresses could mean 20-30 more sales on an email campaign that has a 2-3% success rate.

One very important note. When it comes to newly obtained email addresses, just because a service gave you those addresses, does not mean you have the right to continuously email those people. To keep your spam reports and opt-outs low, I strongly recommend sending an opt-in or opt-out email to all your newly acquired email addresses.

An opt-in is when you send an email asking for those people to reply back with a positive confirmation (or to click a button within the email) allowing you to add them to your marketing database.

An opt-out is the inverse. You send an email telling the newly acquired people to only email back if they want to opt out.

While an opt-out will lead to more people in your database because user inaction will add to your database, an opt-in will likely lead to higher open rates and lower opt-outs down the line because those users will have proactively given you the thumbs-up to be added to your database.

We all have assumptions about who our best customers are. And we are probably accurate to some extent because we work in our businesses every day. But do we have blind spots? I always ask our clients to describe their customers. I often get a response like “Females 25-54” or “Men under 30”. That is because years of buying TV and radio has trained marketers to think that way. But outside of basic demographics you can use your data to determine much deeper demographics and psychographics about your customers.

You can export your data to a service provider (like Digiarks) that will analyze your data and give you back detailed characteristics that are dominant within your database. This can be in the form of affinities (Psychographics like an affinity for luxury items, sports, outdoor activities, etc.) or detailed demographic data. You may be unaware that a large percentage of your clients have children under a certain age. Or that they are empty nesters.

Depending on how big your database is, I’d recommend segmenting your data between customers and prospects, and possibly segmenting your customer database between your best customers and your “average” customers. By doing this you may expose characteristics that are unique to your best customers.

Once you know more about your best customers, make sure you use that knowledge to adjust the way you communicate with them, both in images and words.

A few years back, I was working with a client in the higher education space who learned through a database profile that a large percentage of their graduates had young children. We took that knowledge and added imagery in the advertising and on landing pages that reflected those people and voila - conversion rates rose.

If you know that people who have been your past customers can become your customers again, this is an excellent tactic. Or you may have many records of prospects and past customers who could be in the market for your service. You can upload your data to many digital ad platforms to match your data directly to users in those platforms. This is especially helpful for Social Media advertising.

Facebook and LinkedIn allow you to create “custom audiences” that are made up of people that match records in a file that you upload. Google Ads also has a mechanism for 1-to-1 advertising, but they may limit it to only larger spend campaigns (Can be $50,000 per month).

Earlier I mentioned that “mass” advertising doesn’t often allow you to serve ads to users often enough (frequency) that will allow your message to resonate. When you are advertising on a 1-to-1 basis directly to people in your database, gaining frequency can be a lot more attainable.  

People also tend to be more willing to view content and ads from a business they have previously interacted with. This usually leads to advertising videos being watched to completion more often and higher ad interaction rates.

While you can manually learn about your customers by doing the database profiles mentioned earlier in this article, you can also create “lookalike” audiences in ad platforms directly.

The advantage to this is that you don’t have to complete the additional step of profiling your database. For a platform like Facebook Ads, there are two easy steps. First you upload your database the same way you would if you doing the aforementioned customer match. Then you select the option to create a lookalike audience. Easy peasy.

The downside is that you need to take the platform’s at their word that you are advertising to people that look like your database. It isn’t so much that I don’t trust the platforms. The bigger issue is that you don’t know the factors the platform used to “match” to your users.  As a result lookalike audiences tend to be a “black box”, which I generally try to avoid.

Having said that, lookalike audiences can be a good way to extend your advertising audience beyond your direct data and still have reasonable confidence that your ads are serving to people relevant to your business.