INBOX INSIGHTS, June 16, 2021: How to Address Analytics Shortfalls, USA Job Churn, UTM Order of Operations

How to Address Analytics Shortfalls, USA Job Churn, UTM Order of Operations

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Numbers You Don’t Have

Lee asked an interesting question the other day: “How do you answer a business leader when they ask for numbers that don’t exist?

This was in the context of analytics, of leaders asking to measure things like brand strength, etc. The key to getting around this challenging situation is threefold.

First, at the next available planning session, ask what numbers your business leadership wants to have. There’s a good chance they’ll be fairly common numbers like brand strength (especially versus competitors), ROI, and so forth.

Second, put together a proposal for what it will take to acquire those numbers in terms of personnel and costs. For example, really good brand strength measurement requires always-on surveying, market research, NPS scores, and a handful of other numbers woven together into a brand strength index. For the average midsize to enterprise company, expect to spend low to mid six figures annually to conduct that research.

Third, present the proposal as a sales pitch. Remember that marketing budget is essentially our organization buying qualified leads from us. We’re a vendor, and the budget is what they pay in exchange for our product. These metrics that our leadership are asking for are another product they’re buying.

What happens when we do this? We create choice. We create an opportunity for our leadership to obtain what they want – but at a cost they need to meet. And we create documentation that says, “this thing costs X”. When we come around to reviews and our leadership asks why they don’t have X, if they didn’t purchase it then our response is simple. You don’t have X because you didn’t buy it.

It’d be the same as telling someone who wonders why they don’t have a Tesla in the driveway that in order for them to have a Tesla in the driveway, they need to purchase one. Just as fancy cars don’t just magically appear by wishes alone, neither do metrics and analytics that we haven’t planned to measure.

Treat your measurement as a product that you sell to your stakeholders, and suddenly how you manage it – and them – should be much more clear.

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Binge Watch and Listen

In this week’s In-Ear Insights, Katie and Chris walk through exactly how Google Analytics processes UTM codes, why they’re so important, why Google sometimes gets attribution wrong, and in what order codes are processed – especially when Google Ads is in the mix. If you’ve ever been curious why Google Analytics does the things it does, this is the episode to watch.

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Last week on So What? The Marketing Analytics and Insights Live Show, we looked at how to conduct better research for clients and internal teams for content marketing.

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Data Diaries - Interesting Data We Found

In this week’s Data Diaries, we dig into some jobs data. Jobs data is always interesting because it’s not speculative; no one takes a job as an investment mechanism. They take a job to work and earn money, and when they do so, a chain reaction of events occurs. In the USA, the federal Bureau of Labor Statistics compiles data from companies around the nation and publishes them as data series that anyone can process.

What we want to know is how much churn there’s been in the job market. Churn is the number of new hires plus the number of separations (layoffs, people quitting, etc.) added together. Why measure churn? When you have employee churn, you have a lot of uncertainty and extra costs. New employees cost money to train and may not deliver the levels of service you’re accustomed to. Institutional knowledge gets lost, possibly even transferred to competitors. So how does churn look so far in 2021 in the USA?

Churn in American companies

What we see in terms of industries that have had the highest churn in 2021:

  • Professional business services tops the list of churn; 8.6 million jobs cumulatively have churned this year
  • Accommodations and food services takes second place; 7.47 million jobs cumulatively have churned this year
  • Retail trade is third in terms of churn; 6.1 million jobs cumulatively have churned this year
  • Healthcare takes fourth place; 4.96 million jobs cumulatively have churned this year
  • Manufacturing is in fifth place; 3.1 million jobs cumulatively have churned this year

A quick reminder that we’re measuring jobs, not people. One person who quits one job and joins another is still one person, but that’s two instances of job churn.

All told, the cumulative churn of the workforce is about 50 million jobs year to date, for a workforce population of 261 million people. Think about that for a second – that’s tens of millions of changes to your marketing data.

For B2C marketers, pay special attention to those business sectors like food services, hospitality, and retail. They’ve been substantially impacted by churn, which means lots of opportunity to win new customers – and a struggle to retain existing customers when that much staff is churning.

For B2B marketers, the fact that professional and business services is the highest churning category is worthy of attention. From staff changes to client retention, churn presents substantial challenges.

From a marketing perspective, know that your existing databases have probably aged badly. The pandemic broke many of our mailing lists and CRM databases; last year, we saw more churn than we’ve seen in decades, with more than half of jobs churning in some fashion, 177 million jobs changed in some fashion. This year is calmer by comparison, but there’s still a tremendous amount of job churn.

So what? What should we do about this? From a marketing perspective, make sure you’re running campaigns to constantly keep your mailing lists and databases fresh. Remember that churn is just as much about new employees as it is employees leaving; as someone takes a new job, you have an opportunity to be helpful and useful to them. Take advantage of these higher-than-normal levels of churn to introduce yourself to the new folks.

Methodology: Trust Insights used data from the US Bureau of Labor Statistics via the St. Louis Federal Reserve Bank database. The timeframe of the data is January 1, 2021 – June 16, 2021. The date of study is June 15, 2021. 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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