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Doing The Homework, Community Management, PPP Loan Database

In The Headlights

Learn how to use social media data to improve your SEO in this new paper from Trust Insights and Talkwalker »

Who’s Doing Their Homework?

This past week, we had something of an amusing situation here at the office. One of our goals for 2021 is increased executive visibility for the company, and as part of that, we’d had a discussion with a company that pitches executives to prominent podcasts. We specifically want to get Katie (our CEO) on more podcasts, especially in the areas where she’s got tons of expertise and useful knowledge to share – organizational behavior, change management, marketing in highly-regulated industries, etc. – and that was the substance of the input call with this podcast agency.

A bit of background for those who might not know – John and Chris have been running the Marketing Over Coffee podcast since 2006. We’re on friendly terms with most of the major marketing podcasts, and John was on this input call along with Katie, even introduced himself as the co-host and co-founder of Marketing Over Coffee. The intent of this campaign was to find new, different podcasts for Katie to appear on, to find new audiences instead of the usual crowd.

The call appeared to go well; the agency took in all the information and started to work on the proposal. As part of the pitch, one of their pre-sales deliverables was a short list of just a few shows they would be pitching on Katie’s behalf.

You can guess where this is going. They identified three shows that Katie would be a good guest on:

  1. Scott Brinker’s MarTech Podcast
  2. MarketingProfs’ Marketing Smarts (which Katie has already been a guest on)
  3. Marketing Over Coffee

Needless to say, there’s no point in working with a podcast pitching agency that can’t even do basic homework, like not pitch an opportunity to be on a show with the co-host of that show on the sales call.

While this is a funny story, the underlying message is less funny. This agency didn’t even try to do their homework; if I had to guess, they probably have a media database of some kind, and the most junior person on their sales team was given a single keyword, copied and pasted the first three shows that came up in the results, and sent that out as part of the proposal.

Two takeaways here: first, if you have an agency of any kind doing pitching for you – public relations, podcast guest placement, speaking opportunities – do some digging and see what and who they are pitching. Ask for copies of the pitch emails/outreach efforts and ensure they’re aligned with your brand and message. Too many companies put agencies on auto-pilot, and fire-and-forget is rarely a good strategy.

Second, if you’re doing this kind of work, do your homework! Get to know the space before simply copy-pasting media lists and engaging in spray-and-pray marketing. Spend time listening to the podcasts you plan on pitching. Follow the hosts on public social media channels. Join the shows’ Slack or Discord servers. Once you understand the show and its culture a bit more, you’ll also know whether or not the pitches you’re sending are likely to resonate.

Do your homework. Make sure your agencies are doing their homework.

Oh, and blatant pitch. If you’d like to have Katie as a guest on your podcast, please feel free to ping her in our Analytics for Marketers Slack group or email her at [email protected]

The Bright Idea

In this week’s In-Ear Insights, Katie and Chris discuss the essence of community management. What makes a community thrive? What harms it to the point of dissolution? How do we ensure the communities we’re building are set up for success? Listen in as they diagnose the Analytics for Marketers community and identify things that could be improved.

Watch/listen to this episode of In-Ear Insights here »

On last week’s So What? The Marketing Analytics and Insights Live show, we discussed the basics of data preparation. What constitutes clean data? How should you think about cleaning your data?

Catch last week’s episode replay here »

Coming up on this week’s episode on Thursday at 1 PM Eastern, we dig into part 2 in our data preparation series. Tune in on our YouTube channel below!

Are you subscribed to our YouTube channel? If not, click/tap here to subscribe!

Rear View Mirror Data

In this week’s Rear View Mirror, we dig into an unlikely data source for some insights: the Payroll Protection Program loan dataset. This dataset, published by the United States Government, is a comprehensive list of every company that participated in the Payroll Protection Program of 2020, assistance for businesses during the start of the pandemic.

While the core data – how much a business borrowed – isn’t terribly useful, what this dataset does provide is something far more valuable – a current survey/sample of many of the smaller and mid-size businesses in the United States. While all businesses are required to fill out business census data as part of taxes and annual filings, that data isn’t necessarily as fresh as we would like it to be; some business data lags by years. A fresh dataset like the PPP dataset gives us a snapshot in the moment of how many different businesses there are.

Let’s take a look at some of the basic data:

Businesses by Type

Every business in the US has an NAICS – North American Industry Classification System – code that puts it in one of over 1,000 business categories. Of the 5.16 million PPP loan applications, we see that 3.6% of them came from full-service restaurants, followed by law firms, real estate firms, doctors and dentists, and beauty salons.

Gender and Veteran

Within the dataset, we see gender types for the kinds of businesses owned; the vast majority of businesses do not declare ownership by gender. What we do see is that of the businesses that do declare it, male-owned businesses are 3.36 times more prevalent.

Ethnicity

The vast majority of businesses also do not claim an ethnicity for ownership; of those that do, White-owned businesses are most prevalent, followed by Hispanic, Asian, and Black businesses.

Corporate Type

Finally, we see the different types of corporate structures, with the largest type being the C Corporation, followed by LLCs, then sole proprietorships.

What do we make of all this information? What purpose does it serve? Within the data, each business also has its postal address, number of employees, and other pertinent basic demographic data, all in one handy database. If your company is a B2B business, this is a goldmine for identifying local businesses by size and industry, then developing a list of those businesses you might want to design marketing programs for.

For anyone interested in social justice issues, this database is a helpful who’s who of local businesses you could support by ethnicity or gender, should that be of interest.

And for anyone interested in data science, this is a great starter database that’s reasonably well-structured – and the insights you generate from it will not only be good exercises for skill development, but have practical applications as well.

Download the dataset for free here.

In Case You Missed It
Partner Spotlight

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Shiny Objects

Shiny Objects is a roundup of the best content you and others have written and shared in the last week.

Data Science and AI

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Content Marketing

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Get Back To Work

We’ve changed things up in Get Back To Work, and we’re looking at the top 310 metro areas in the United States by population. This will give you a much better sense of what the overall market looks like, and will cover companies hiring in multiple locations. Get all the data in our Slack group!

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