INBOX INSIGHTS: CEOs and Generative AI, 2023 Holiday Retail Season Planning (9/13):: View in browser
What Do CEOs Need to Do About Generative AI Employee Concerns?
You’ve read plenty of articles about what C-Suite needs to know. And you’ve heard the concerns from employees about generative AI. But have the two conversations converged?
CEOs and other C-Suite positions are buzzing about the possibilities of generative AI. Employees are losing sleep over wondering how they will stay skilled up on AI and keep their jobs.
There is a disconnect from what the C-Suite is doing and how they are communicating (or not) with the the rest of the company.
What do CEOs need to do about employee concerns?
This is the first order of business. Too often, leadership teams have closed doors and closed lips about what’s going on. Employees pick up on that, despite how well leadership thinks they are playing it cool. Be open about AI intentions for the company, implementations, and implications. Be up front with them. If you don’t know what it means for the company yet, say so. That will go a long way to building trust rather than waiting until you figure it out.
Education and Training:
If you, the leader of your organization, decide that generative AI is the direction, you need to help your employees get up to speed. Offer training sessions to help employees understand AI and how they’ll use it. Empower them to work with, rather than against, these systems. Bring in outside trainers and experts to help your employees with their professional development. Have a clear idea of what you want them to do with generative AI so that you can focus the training sessions.
Reassure Job Security:
As the new, or old, saying goes – AI won’t replace jobs. People who know how to use AI will replace the roles of those who don’t. This goes back to the first point, transparency. When you’re introducing high profile tech like AI, you need more frequent and consistent reassurance. AI is getting more sophisticated by the day and the fear over job security continues to heighten. Without knowing what’s going to happen, employees with start to leave. You need to stay ahead of the turnover by having conversations with your employees.
One of the biggest mistakes leadership teams are guilty of is making decisions without consulting the people who need to do the work. Create a space where employees can weigh in on how they could and should use generative AI. This will help shape the roadmap but also give people a sense of ownership. Make sure you’re really hearing the feedback and not just paying lip service.
I have been encouraging leaders to start with their mission, vision, and values. Introducing tech such as generative AI needs to align with those initiatives. Additionally, AI is not perfect. In fact, it’s riddled with bias and other potentially non-ethical errors. Why? Because it’s a tech created by humans, and generative AI is a reflection of those humans. Make sure you do your homework to ensure that the AI you out in place adheres to ethical standards. If you’re not sure what that looks like for your organization, that’s where you should start before choosing a tool.
As the CEO, CMO, Director, or other decision maker, you’re setting the tone for your employees. Stay open, listen to your teams, and communicate early and often.
Are you considering bringing generative AI into your organization? Reply to this email to tell me about your journey, or come join the conversation in our Free Slack Group, Analytics for Marketers.
– Katie Robbert, CEO
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In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss the important issue of who owns your data. They talk about why companies need to be aware of who has access to their data, especially when using tools like Google Analytics or generative AI models. Katie and Chris explain how you may be giving competitors access to your data indirectly through models trained on your data. They offer suggestions for ensuring you maintain control and ownership of sensitive company data when leveraging new technologies like AI. Tune in to hear their examples and recommendations for governance, collaboration, and setting up the right data architecture.
Last time on So What? The Marketing Analytics and Insights Livestream, we explored identifying generative AI use cases using a 2×2 matrix. Catch the episode replay here!
This Thursday at 1 PM Eastern on our weekly livestream, So What?, we’ll be examining customer satisfaction data and what we can learn from it. Are you following our YouTube channel? If not, click/tap here to follow us!
Here’s some of our content from recent days that you might have missed. If you read something and enjoy it, please share it with a friend or colleague!
- In-Ear Insights: Who Owns Your Data?
- AI-Driven Pumpkin Spice
- So What? Identifying Generative AI Use Cases using a 2×2 Matrix
- AI-driven versus Artisanal
- INBOX INSIGHTS, September 6, 2023: When ChatGPT Goes Sideways, Content Curation Systems
- In-Ear Insights: The C-Suite Guide to Generative AI
- Almost Timely News, September 10, 2023: Avoiding AI Point Solutions
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Now that Labor Day has come and gone in the USA (for non-USA folks, it’s the end of summer and return to work for many), it’s time to start thinking about the tail end of the year. While we shared a lot of information in general about Q4 in our Data-Driven Marketing Planning Guide, let’s look at retail specifically. When is the 2024 retail season going to kick into high gear?
We run these forecasts using years and years of back data, including pre-pandemic because searches about holiday gifts are durable. Pandemic or not, people didn’t stop shopping for gifts for the people they care about, and while the methods of shopping may have changed over the years, the intent has not. We use search data around terms like “holiday gift guide” and “gift ideas” (plus about a dozen others) to build a forecast that looks ahead.
When does the holiday retail season begin?
We see that searches for gift ideas and associated concepts begin in mid-October this year, around October 15. Things really kick into high gear the week before the Thanksgiving holiday (orange vertical line), and peak in the second week of December before the Christmas holiday (red vertical line). One unusual thing in this year’s forecast is that searches drop dramatically in the week before the Christmas holiday; in years past, gift idea searches continued up to the last minute. We don’t know why that would be the case, but that’s what the algorithms concluded from the search data.
So what do we do with this information? It depends on your role in your organization.
If you’re in a public relations role, NOW is the time for long-lead publications. If you want your products included in retail guides, you’re technically about a month too late, but you might be able to get listed in some shorter-lead holiday guides.
If you’re in marketing, you have about a month to get all your campaigns budgeted, staged, and ready to deploy.
If you’re in HR, you now have a roadmap for what kind of staffing needs you’ll require. If the staffing levels you have planned in September are already pushing the limits of a good customer experience, by mid to late October, you’ll be overwhelmed if you maintain the same levels.
If you’re in finance, you’d compare this year’s forecast to the previous years’ data and your actuals at the register to better assess the kind of revenue you might expect from this holiday season.
And this is the key to using data, the most important part. Data shouldn’t be siloed in one part of your organization – especially if that data is a forecast. One forecast has benefits which cross organizational functions, from HR to finance to marketing. Avoid letting valuable data get trapped within the walls of a single department – part of data governance isn’t just managing who shouldn’t have access to some data, but also who should.
- Case Study: Exploratory Data Analysis and Natural Language Processing
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Here’s a roundup of who’s hiring, based on positions shared in the Analytics for Marketers Slack group and other communities.
- Abm Specialist at Campaign Monitor
- Data Analyst at Aller Media A/S
- Data Science Architect at APPIC Solutions
- Digital Marketing Manager at Etsy
- Director, Sales Emea & Apac at Customer.io
- Technical Account Manager at Snowplow Analytics
- Technical Account Manager at Snowplow Analytics
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