Marketing Data Dump: Analytics, Big Data, and The Internet of Things

One of the biggest issues with the Industrial Internet of Things (IIoT) is that more and more data is gathered as it begins to affect more businesses. The amount of data can seem overwhelming, and the data dump can seem like you are trying to get a drink from a fire hose.

How do you take all of that data and transform it into something that is actually useful to your business? The key is analysis: taking only the data you need from that generated by the IoT, and sorting it into what you can really use to improve your marketing efforts.

There are many sources where you might gain data: from simple public census data to that generated by wearable technology, fitness apps, search engine algorithms, and more. Data can be taken from your industry or your enterprise depending on the level of detail you actually need.

When you boil it all down to the data about who your marketing efforts are reaching and how they are reacting to it, you can then ask yourself some very useful questions.

Who is your target?

Even before you start a marketing campaign, you can use industry and search engine data to help you create a more accurate marketing persona. Who is your ideal customer? Ideally, you will have more than one, but which one is this campaign trying to reach specifically?

You can reach a broad target with a marketing campaign, but you need to ask yourself some key questions:

  • What pain points does this persona have? In other words, what problem does the product or service you are offering in this campaign solve for them, or what need or want does it satisfy.
  • Where have they found solutions in the past? Does this persona buy online or in stores?
  • Where are they in the sales funnel? Is your target at the beginning of their buyer’s journey, still looking for potential answers, or are they ready to buy? This will determine what content they land on first on your site, and how you need to direct them with your campaign.
  • Are they new prospects or existing customers in this space? Even if they have not purchased goods from you before, they may have done so from your competition. What can you do to win them over?

The more you know about your target, their buying habits, and how you can best reach them the more likely you are to be successful.

Did you Hit or Miss?

Once you have completed a campaign or two, your own enterprise data can tell you a lot about your customer, and they are providing you with it through their continued use of the internet of Things. The first couple of ways you can determine if your marketing hit or missed is to look at a couple of basic things.

First of all, did you reach the demographic you were targeting? If your campaign was directed particularly at career women between the ages of 35 and 45, is that who most of your buyers are?

Secondly, when you look at how buyers are using your product, was that intention? Are they using it the way you envisioned or another way entirely? Often in the case of software or other products and services, we will find that our customers have something in mind entirely different than what we had in mind.

This leads us to our next step in our analytical process.

Shift Fire or Change Targets?

If our customers are using our products in a different way than we thought, or we have reached an entirely different audience than we anticipated, we need to determine if that if the flaw is in our marketing, and we have reached the wrong audience, perhaps leaving out an important one.

On the other hand, perhaps we need to shift our focus to the audience we have reached. Perhaps in our initial analysis we were wrong about who would be most interested in our products and the way they could be used.

It may be that neither of these are the solution, and instead the answer is to launch a new campaign to reach our original intended audience, shifting our target from who we did reach to who we originally targeted. At the same time, we can continue with our current efforts, and continue to reach an unanticipated audience.

This potentially gives us the best of both worlds as long as each audience is large enough to justify our investment in them, and we get a significant ROI from each.

Who Did You Leave Out?

The final analysis of the big data we get from the Internet of Things can help us determine who we left out with our marketing efforts. If in our industry, an average of 60% of customers are male, and in our case 60% of our customers are female, that may mean we are missing out on a whole segment of men who would buy our product or use our service if they were aware of it.

This means we are missing a large potential segment of the market that our competitors have found a way to reach. We need to look at both what we are doing and what they are, and see what we are missing.

However, use some caution in using your analytics here. It could be that you have reached a market segment your competition is unaware of, and you have tapped into a new pool of customers. When comparing your data to that of the industry, be sure you are comparing like to like. Your data and your customer base may be unique.


The Internet of Things can produce a pile of Big Data that feels like a Data Dump. It may feel like you are trying to get a sip of water from a fire hose. But by narrowing it down and gathering and analyzing only the data you need for your project, you can not only make it manageable, but you can also make it work for you. Was this article helpful? Leave us a comment in the section below.

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