In The Headlights: August 26, 2020 Issue

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In The Headlights

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Predictive analytics can’t predict right now.

That seems like a strange admission for a company where predictive analytics is a core service for clients, but it’s also the stark truth. Right now, any kind of time-series forecasting is highly unreliable for outlooks more than a couple of weeks in advance. Why? Because the macro environment we’re all operating in is incredibly unstable. We’re in the middle of a global pandemic, which has also ushered in a global depression the likes of which we haven’t seen in a century, combined with multiple conflicts and heightened instability planet-wide. The net effect of this environment is that everything is up in the air right now, and no one has any meaningful ability to forecast what’s going to be happening in 6 months or more.

This holds true for virtually everything – even trends and forecasts that were once stable, like holiday gift guides or real estate markets. For example, in the United States, the real estate market is currently in the middle of a boom despite countervailing economic trends. Can we realistically predict what the market will look like in 3-6 months? Not at all – the economic impact of discontinuing federal pandemic assistance is still unclear, though basic logic and deduction would suggest millions of people suddenly without meaningful income will not be an economic positive.

So, what do we do in an environment like this? Many companies are beginning their budgeting and annual planning cycles now. How do you realistically set a budget for the year ahead when the outlook for the year ahead is as opaque as a San Francisco harbor fog? We recommend two approaches.

First, pay attention to your short-term analytics as an ongoing process. If your reporting cycle is typically monthly or quarterly, trim down the metrics you pay attention to until you’re working with three or fewer essential KPIs and report on those weekly, if not daily. You’ll adapt to changing conditions much more quickly if your reporting is more lean and faster. A basic dashboard like a Google Data Studio dashboard, set as the home page of your browser, is an easy way to help you keep an eye on your data every day.

Second, for planning and forecasting, we recommend four scenarios and plans:

  1. Best case scenario, which looks an awful lot like February 2020, before the pandemic. A vaccine is discovered and rapidly distributed fairly, enabling everything to open up once again
  2. Worst case scenario: what’s realistically the worst that could happen to your industry? For many of us, that looks like 60-75% loss of revenue. If large swaths of our populations can suddenly no longer afford the basics, we’re looking at a depression that’s actually unprecedented (in the United States, the Great Depression clocked around 25% actual unemployment)
  3. Current course: what’s likely to happen if current conditions continue to muddle on as they have been? That might mean operating on reduced budgets and staffing, but no other major shakeups as we patiently wait for things like vaccines to ameliorate the crisis
  4. Most probable outcome: this is the scenario that requires the most research on your part. What are the probable events – and they’re extremely difficult to discern – that the next year will bring?

Based on these scenarios, what’s your plan for each? What’s your budget for each? Having each option carefully planned out will give you maximum flexibility to react to changes as they happen. Suppose, for example, in the region you operate in, a massive tropical storm devastates the area. If you were operating on a current course scenario, you’d pull out the worst case scenario playbook and begin executing from that, rather than having to plan on the fly, in the middle of an emergency.

When it comes to things like budgets, ask for the most while developing at least one plan that has little to no budget. That way, you have resources to work with as you adapt plans – work out budgets for each of the four scenarios above, and ask for the budget that’s the largest, filing your plan for that scenario along with it to justify it.

While we can’t predict with analytics right now, we can plan with probabilities. Use this framework to build your 2021 forecasts and plans!

The Bright Idea

In this episode of In-Ear Insights, Chris and special guest John Wall discuss the state of consumer recommendation engines. Why are recommendations so narrow and ineffective many times? What could we do to improve them beyond what we get now? Listen in as we discuss limitations of computational power, algorithm choice, and more.

Watch the discussion now!

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Rear View Mirror Data

In this week’s Rear View mirror, we take a look at the state of content. We’re a full six months into this pandemic and the holiday season is just four months away. What are the characteristics of top performing content?

Data

See something unusual? We certainly do. Compared to previous studies of top performing content, content that’s done well in the six months since March 2020 is decidedly shorter, and has earned substantially less traffic. Looking back at March 2020, the median traffic articles earned was around 100 visits; here it’s 15. The median shares now is close to 2,000, where in March it was around 1,000. And the length of content has changed drastically, from a median of 550 words to a median of 375 words.

These numbers are substantial changes, changes that indicate a change in behavior – people seem to be sharing more while simultaneously reading less, and content has shortened by 32%. Why? When we look at the word cloud of top-performing content, the type of content mentioned becomes apparent. It’s a video world, from Netflix to video games to adult entertainment.

What’s the key takeaway? We don’t know whether the change in behavior represents a permanent change or not, but the obvious conclusion is that if you haven’t built a robust video marketing strategy to earn a place in your audience’s video consumption habits, you’re behind the curve. Now is better than never – if you don’t have one, get started today.

Methodology: Trust Insights used the AHREFS SEO software to examine a sample of the top 187,216 articles on the web by traffic since the start of the pandemic in the United States. The dataset is limited to articles in the English language, chosen by the top 25 stopwords in article titles. The dates of extraction are March 15, 2020 – August 25, 2020. The date of study is August 26, 2020. 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.

In Case You Missed It
Partner Spotlight

AI Academy for Marketers is an online education platform designed to help marketers understand, pilot, and scale artificial intelligence. The AI Academy features deep-dive Certification Courses (3 – 5 hours each), along with dozens of Short Courses (30 – 60 minutes each) taught by leading AI and marketing experts.

Join Katie Robbert, CEO of Trust Insights, and Christopher Penn, Chief Data Scientist of Trust Insights, for three separate courses in the academy:

  • 5 use cases of AI for content marketing
  • Intelligent Attribution Modeling for Marketing
  • Detecting and Mitigating BIAS in Marketing AI

The Academy is designed for manager-level and above marketers, and largely caters to non-technical audiences, meaning you do not need a background in analytics, data science or programming to understand and apply what you learn. One registration gives you unlimited access to all the courses, an invitation to a members-only Slack Instance, and access to new courses every quarter.

Join now and save $100 off registration when you go to TrustInsights.ai/aiacademy and use registration code PENN100 today.

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

SEO, Google, and Paid Media

Social Media Marketing

Content Marketing

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. Want the entire, raw list? Join our Slack group!

What do you do with this information?

By looking at this data, you’ll see what the most popular titles are; use any of the major job/career sites to ensure your resume/CV/LinkedIn profile matches keywords and phrases for those titles. For companies, search job sites for those companies specifically to see all the open positions and apply for them.

You can also hit up LinkedIn and see who you know at companies listed, and see if your connections have any inside tips on hiring.

Top Marketing Positions by Count, Manager and Above

  • Marketing Manager : 472 open positions
  • Digital Marketing Manager : 272 open positions
  • Social Media Manager : 198 open positions
  • Account Manager : 193 open positions
  • Director of Marketing : 158 open positions
  • Project Manager : 138 open positions
  • Marketing Director : 136 open positions
  • Product Manager : 109 open positions
  • Product Marketing Manager : 98 open positions
  • Program Manager : 87 open positions

Top Marketing Hiring Companies by Count, Manager and Above

  • Amazon.com Services LLC : 158 open positions
  • Pearson : 124 open positions
  • Google : 108 open positions
  • Mattel : 82 open positions
  • Amazon Web Services, Inc. : 73 open positions
  • Northrop Grumman : 64 open positions
  • Deloitte : 61 open positions
  • Thermo Fisher Scientific : 60 open positions
  • Flosum : 45 open positions
  • T-Mobile : 45 open positions

Top Locations of Hiring Companies by Count, Manager and Above

  • New York, NY : 621 open positions
  • Austin, TX : 413 open positions
  • San Francisco, CA : 394 open positions
  • Chicago, IL : 361 open positions
  • Seattle, WA : 303 open positions
  • Atlanta, GA : 297 open positions
  • Boston, MA : 252 open positions
  • Los Angeles, CA : 241 open positions
  • Remote, NA : 226 open positions
  • San Diego, CA : 216 open positions

Methodology: Trust Insights uses the Indeed.com API to extract open positions from a geographic area focused on marketing analytics, marketing, social media, data science, machine learning, advertising, and public relations, with a filter to screen out the most junior positions.

Our Featured Partners are companies we work with and promote because we love their stuff. If you’ve ever wondered how we do what we do behind the scenes, chances are we use the tools and skills of one of our partners to do it.

Join the Club

Are you a member of our free Slack group, Analytics for Marketers? Join 800+ like-minded marketers who care about data and measuring their success. Membership is free – join today.

Upcoming Events

Where can you find us in person?

  • INBOUND 2020, September 2020, virtual
  • MarTech East, October 2020, virtual
  • MarketingProfs, November 2020, virtual
  • MadConNYC, December 2020, New York City

Going to a conference we should know about? Reach out!

Want some private training at your company? Ask us!

In Your Ears

Would you rather listen to our content? Follow the Trust Insights show, In-Ear Insights in the podcast listening software of your choice:

Stay In Touch

Where do you spend your time online? Chances are, we’re there too, and would enjoy sharing with you. Here’s where we are – see you there?

Required FTC Disclosures

Events with links have purchased sponsorships in this newsletter and as a result, Trust Insights receives financial compensation for promoting them.

Trust Insights maintains business partnerships with companies including, but not limited to, IBM, Talkwalker, Zignal Labs, Agorapulse, and others. All Featured Partners are affiliate links for which we receive financial compensation. While links shared from partners are not explicit endorsements, nor do they directly financially benefit Trust Insights, a commercial relationship exists for which we may receive indirect financial benefit.

Conclusion

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