INBOX INSIGHTS, April 6, 2022: The Unaware Audience, GA4 Implementations, Women-Owned Agencies

INBOX INSIGHTS: The Unaware Audience, GA4 Implementations, Women-Owned Agencies (4/6) :: View in browser

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The Unaware Audience

“How do I get more leads?” is usually the first question we hear from prospects and clients. It’s a great question to start with, but it’s not the only question you should be asking.

If you’re in the B2B segment, you know that it functions differently from B2C efforts. There is a lot more education that needs to happen before you can go straight to “I want to buy this now” – especially if you run a services agency.

The piece that we’re missing, me included, is reaching the unaware segment of our audience before they can become leads. We’ve been pouring over our own monthly reporting, trying to figure out what we’re missing. What we’re missing is a lot of activity at the top of our funnel.

Trust Insights is really good at helping people solve problems when those problems are known. We are not so great at attracting an audience of people who only have symptoms and are unaware of the actual problem.

Gini Dietrich gave me this clear cut example of what I was trying to articulate about the unaware audience:

I actually just heard a commercial in the car this morning that was interesting. It’s for an ear, nose, and throat doctor. They talk about how if something is going on, you call your primary doc then they refer to you an allergist who does a bunch of tests only to figure out you don’t have allergies so you go back to your primary doc who suggests more doctors and more tests. But with this place, you have a stuffy nose or an earache so you go to them and they figure out the root cause on your first visit.

In this example, Trust Insights is the ENT, and we want people to come directly to us, even if they just have a stuffy nose. Why? Because we’re specialists. We know that a stuffy nose is part of the story and we have a whole set of questions to ask that will narrow down the diagnosis and get to the root issue.

When we take that example and start to translate it to marketing, a stuffy nose becomes a data point that doesn’t look right. A sinus headache becomes missing data. And so on.

This brings me back to the point, you need to be able to educate the unaware audience on the symptoms so that they will come to you for help, aka, “How do I get more leads?”

In the latest CMO Survey, we know that customer want superior product quality, excellent service, and a trusting relationship:

CMO Survey

Start with education. This is through your blog and other content. This content should introduce who you are, what you do, and your expertise. We ALL jump too quickly to wanting people to buy from us so we skip over the awareness stage. Without awareness, people won’t buy. Couple that with an attribution report and you’ll know which channels to publish your awareness content on.

Don’t skip over the relationship-building phase and assume it will come once a contract is in place. So, my advice to you (and me) is to spend more time getting to know your audience. Don’t go in with the hard sell. Really listen to what they are saying, the questions they are asking, and help them put the pieces together for themselves. The leads will come. They will be the people that you helped understand their symptoms. The people that trust you to provide the answers.

How do you reach the unaware audience? Let me know in our Free Slack Group Analytics for Marketers »

– Katie Robbert, CEO

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Data Diaries - Interesting Data We Found

In this week’s Data Diaries, let’s talk through solving a data problem. I recently had the chance to sit down with Christy Hiler about women-owned ad agencies. One of the questions that came up was – well, how do we know how many women-owned ad agencies there are?

Take a moment to ask yourself: how would you solve this problem?

Any time we’re faced with a data problem, we need to know 5 things:

  1. What’s the outcome we want?
  2. What’s the process for generating that outcome?
  3. What skills and people do we need?
  4. What tools and technologies do we need?
  5. What data do we need?

If we don’t have clear answers to all five questions, we’re not going to be able to solve the problem well.

We know what the outcome should look like – a summary of ad agencies and their ownership structures. That’s fairly straightforward – and in something like a bar chart to make it easy to understand.

Let’s hold off on process and technology for a bit. Do we have the right people? The specific skillset we’re after is exploratory data analysis. We need someone who can take data, explore it, and deliver some reasonable conclusions about it. But we also need subject matter expertise in data about companies – without that, we’re in for a long, often fruitless amount of Googling.

Now, what data do we need? Here’s where subject matter expertise helps. In this instance, we’re talking about company data, and the scope of the data is companies in the United States. If you know the US government data systems well enough, you know that most government agencies publish non-classified data fairly freely. For this exploration, we need a comprehensive view of all companies in the USA.

If you recall from a couple of years ago, the US government made a massive number of loans to businesses of every size at the start of the pandemic as part of the Payroll Protection Program, and published that data for anyone to see. Many, many companies took that assistance, and thus the Payroll Protection Program represents the single largest survey of business in the USA ever done.

So now we have the data we need. What technology do we need to manage it? The entire dataset, downloaded, is about 5.8 GB of data – not a trivial amount and much more than off-the-shelf tools like Excel can handle out of the box. It’s made more complex by the fact that it comes in 15 volumes, like an encyclopedia. For this, we’ll need a heavy-duty data management tool like Python or R.

Finally, what’s the process for exploring this data? Exploratory data analysis is exactly that – exploring data to see what’s available. It’s practically a discipline of its own; to do it well, we need to be versed in things like anomaly detection, descriptive analytics and statistics, and visual communication of data.

What did we find after processing more than 11 million records?

Agencies by type

For all but public relations agencies, of those agencies that specified a gender of ownership, male-owned agencies were the norm. Above, a ratio of 1.0 would indicate equal ownership – a 50/50 split. Below 1.0 means there are more female-owned than male-owned agencies, and above 1.0 means there are more male-owned than female-owned agencies.

This is the power of exploratory data analysis – and how challenging it can be. The preparatory work of answering those 5 key questions cannot be overdone – having clear outcomes, processes, skills, tools, and data are essential. You can’t skip steps or cut corners and still have a valuable analysis by the end.

Methodology: Trust Insights extracted 11,468,861 records from the US Small Business Association Payroll Protection Program site, filtering for NAICS codes for agencies. Addresses were normalized and then records were de-duplicated. The timeframe of the data is June 1, 2020 – March 22, 2022. The date of the study is April 6, 2022. Trust Insights is the sole sponsor of the study and neither gave nor received compensation for data used, beyond applicable service fees to software vendors, and declares no competing interests.

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