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DIY Enterprise-Level Marketing Data For Every Size Business
Think big data is only for big companies? Columnist Alistair Dent demystifies the buzzwords and explains how even scrappy smaller businesses can employ cutting-edge techniques.
If you’ve been reading these pages, you’ve heard a lot about omni-channel marketing, data integration, and other tech-driven marketing buzzwords.
But you might be getting the impression that only the Amazons and Apples of the world have the resources to take advantage of the marketing techniques and insights enabled by this data. Well, you’re wrong.
Read on for more and keep tuning in for the next installments in this series. We will cover the current data landscape in marketing; how enterprise-level marketers use data to improve their branding and performance; and finally, how you can start to immerse yourself into this world with the free (or nearly free) tools available.
Every four weeks, I’ll discuss another puzzle piece in the data landscape, what it means for marketers and what you can do yourself. First of all, I’ll introduce the component parts and then discuss first-party data.
Data Sharing For Better Results
A common trap that advertisers fall into is to assume that data sharing across their marketing activity is helpful for optimization and attribution but nothing else.
Anyone who has looked at attribution data knows that’s not the case: people’s paths to conversion are varied and, frankly, a bit insane.
Activity you consider branding gets touched by prospects at every point in their journey, and it needs to do a job of supporting the sales cycle.
Your performance “end-of-funnel” marketing may just as easily be the first awareness-generating touchpoint and needs to be able to act accordingly. In this environment, branding does a performance job, and performance does a branding job.
If you use data purely for performance-oriented campaigns and leave it out when you design your branding efforts, then you’re failing to achieve the secondary goals of both types of initiatives. Ignoring data at any stage means you’re wasting portions of those budgets. More on that later.
For now, consider how important it is that your branding activity works together with everything else you do. If every touchpoint a user has with your brand tells a consistent story that is relevant to the user’s need at that moment, you’ll improve on all your KPIs.
The Right Story To The Right People At The Right Time
This sounds vague, right? This is the kind of phrase used by offline marketers or media owners. We performance people know that kind of stuff doesn’t matter — I just need to be able to manipulate my bids, optimize my targets and rotate my ads.
We’re wrong, and they’re right; it just took years for the technology to catch up.
People give us signals all the time. Every move they make online (and sometimes offline) helps build our picture of what’s important to that person. By collecting and analyzing that data, we learn which messages resonate with which groups of people.
Those signals might be indicating that they’re a family with children. They might be telling us from their search term that they want a BMW. Their browsing history could tell us they really want to go skiing.
It’s up to us to read those signals and react appropriately. So long as each of our marketing channels works together rather than in isolation, we can treat that individual the right way throughout their journey with us.
Doing This Properly Is Complicated
Sorry about that; it’s simply unavoidable. These channels don’t work well together, but it’s valuable when they do. Those challenges mean there is a huge landscape of companies trying to make things better.
That’s good because it allows us to do clever things. But it means another group of people is in the middle trying to make a margin. Since this is so difficult, demand is more aggressive than supply, and the costs can be prohibitive unless you’ve got a lot of clout. It’s still worthwhile.
What I’m going to focus on through this series of articles is what this data landscape enables you to do, and what you can manage without enterprise-level resources.
What Can I Do Myself?
A surprisingly large amount, actually. Which is good news. Tag management and web analytics are the core tools you’ll need, and you’ll need to employ a developer who is comfortable with the way that marketing systems can interact.
You won’t be able to have the same depth of information on every customer or prospective customer, but by focusing your efforts on just the highest impact areas you can get a lot of the benefits.
What Does The Landscape Look Like?
This is a big question. I simply cannot cover the entire landscape, and if I tried, by the time I finish writing this paragraph, it’ll be out of date.
What I can do is introduce the different categories of data and the important types of players in those markets. I’ll introduce what they each are; then with future columns, I’ll go into much more detail about each category.
We can consider data falling into three categories: first-party, second-party and third-party. These aren’t necessarily clear splits, but a safe way to break them down in your mind is as follows:
First-Party Data. This data is the information you own about people’s interactions with your own brand. Basically, this happens on your properties like your website or your app, or the clicks on (some of) your own adverts.
AdWords data falls into this category, as does your Google Analytics data.
Second-Party Data. This data generally involves a direct relationship between you and another party involved in the process.
This is the kind of data that arises from sitting down in a room with the other party and agreeing what is to be shared and how. Users usually must agree to this more explicitly, since it involves disaggregated information being shared.
This data covers things like the information that the publisher of a display placement passes to you, or shared remarketing lists between yourself and another company.
Third-Party Data. This data is almost always private and aggregated. Personal data is too sensitive to share, but very valuable. So, data brokers will strip the identifiers and sell you aggregated stats.
You can use this to help optimize toward certain demographics or to restrict your media targeting away from the poorest prospects.
Data Sharing Technology
CRMs, web analytics, app analytics, DMPs… These tools collect, store, process and share data to let you link this all together.
- CRM. Customer Relationship Management. Your own data store about your customers
- Web Or App Analytics. This is how you collect a user’s interactions with your own properties
- DMP. Data Management Platform. This single source of truth acts as a data warehouse for all your data sources, but links them together to enrich them all.
Data Utilization Technology
This tends to fall into two categories: technology for improving targeting or technology for improving creative. In the former category, we will focus on DSPs — Demand Side Platforms.
It’s a pretty generic name for quite a specific tool; this is a campaign management tool that lets you utilize all the data available in order to buy the right media inventory.
Ad servers fall into the latter category. Modern ad servers let us link many data sources to choose which ad we show to which user.
Once we’ve bought the inventory through our DSP, we send those signals to the ad server so that we know we’re showing the right ads in the right order to the right people. Awesome.
Next time, we’ll really dive into the meat and start looking at first-party data: where it comes from, how to track it, how to combine different sources and how to use it, including search to display retargeting.
Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.