INBOX INSIGHTS, October 4, 2023: Technology and Connections, Generative AI for Tasks

INBOX INSIGHTS: Technology and Connections, Generative AI for Tasks (10/4) :: View in browser

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Technology is a Barrier to Connection

I recently started a new volunteer position at a local animal shelter. My primary responsibility is to tend to the dogs that are in the shelter. Make sure they have fresh water, fresh bedding, take them for walks, or just sit with them. My job isn’t to tell them what they need, but to help re-establish trust so that they are adoptable and can move onto the families they deserve.

This work is hard. This work is heart breaking. But this work is rewarding. This is the same reason I focus so much on people management. It can be hard work. It can be heart breaking. But it can be incredibly rewarding when you see someone succeed.

As I was sitting with some of the shelter dogs, working on rebuilding their trust with humans, it occurred to me that we are at risk. We are so reliant on technology, like generative AI, that we’re forgetting how to build relationships and trust with each other.

And you cannot outsource building relationships and trust to a machine. You just can’t.

No, this is not a new problem. With each technological innovation we create obstacles, barriers, and excuses for people not to interact with each other. Generative AI is only adding to that. The difference is that instead of just putting up a technical barrier between people, generative AI cuts other people out all together. When you use your phone to text someone, you’re still talking to another person. When you’re using generative AI, you’re not interacting with another person, you’re talking to a machine. This machine won’t give you feedback on your tone, on your conversation, or on your output. It will just do what it’s asked.

And this is the risk. You don’t have to spend time with generative AI to build trust. You don’t have to say things like, “please” and “thank you” to get an output. As humans, this will allow us to lose all our people and conversation skills.

There are a lot of experts, Trust Insights included, that want to educate on how to craft the best prompts for generative AI. What to include in your requirements to get the best possible outcome. How to interact with generative AI to make it work for you.

What if you spent that much effort into your human interactions? You assessed the needs and approached the conversation in a way that would lay the foundation of what you want to achieve. Then you kept working at it, kept refining based on the output to continue getting better results.

When I was at the shelter, no two dogs behaved the same. I needed to tailor my approach to each situation. I had to gather information, mentally build my requirements, and then adjust as I learned more. When working with Dexter, the 11 year old meatball, I could be more hands on and playful. With Gracie, the shy and timid pup who has grown up in shelters, I had to avoid eye contact and keep my distance. With Joe, the 100 lb German Shepherd who was all energy, I had to assert more dominance and help him learn to be patient.

When you’re dealing with humans, you’re unlikely to find two that will behave the same or even consistently. You will encounter the extroverts, the shy ones, the energetic ones, and the more relaxed ones. You will learn over time what works when interacting with different people. People will change over time. Your approach will adjust but you will learn more. You will deepen the relationship and strengthen the trust. When you’re dealing with machines, you’re more likely to get consistent results, but no feedback on how to better adjust your approach. You won’t have a relationship. You won’t have trust. You’ll have you. And you’ll have a machine.

All this to say, the more time you spend only interacting with machines, the more your people skills will fade away. If you don’t feel like your people skills are strong, use generative AI to practice. Ironic, I know. But instead of treating it like the machine it is, talk to it like a human. Interact with it the way you would a person, but also ask for feedback. In you prompt, tell it that you’re wanting to develop your communication skills. Let it know that you want it to behave like a person would.

Despite what Chris might say, people aren’t going anywhere and you have to learn to deal with them. They are the ones that build and manage the machines. They are the ones making decisions about our government, our rights, our health. Learning to work with, instead of against, people will be a skill that companies will covet. It will become harder to find and even harder to master.

So start now. Hone your people skills. Learn how to be a stronger communicator. Master the art of management. We will only see more technological barriers put up, preventing us from connecting. It will get harder. But it is not impossible.

If you want to learn more about how to talk to people and you’re at #MPB2B in Boston, swing by my session: Managing the People who Manage the Machines. I’d love to see you!

If you’re not at #MPB2B this year and want to continue the conversation, reply to this email or come join the conversation in our Free Slack Group, Analytics for Marketers.

Delta from Baypath

And if you’re interested in learning more about the dogs I mentioned, you can find them here.

– Katie Robbert, CEO

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Binge Watch and Listen

In this episode of In-Ear Insights, the Trust Insights podcast, Katie and Chris discuss generative AI adoption in business and how leaders can put effective guardrails in place through understanding employee needs and setting clear expectations.

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

Last time on So What? The Marketing Analytics and Insights Livestream, we talked through crisis communications with special guest Gini Dietrich. Catch the episode replay here!

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Data Diaries: Interesting Data We Found

It’s monthly reporting time, and monthly reporting is one of the greatest opportunities for us to find efficiencies. How long does monthly reporting take you?

For me, doing reporting for our clients takes about a day, sometimes two days to process all the data and turn them into reports. Every month, I’m always on the lookout for ways to save additional time, to shave time off the process. Why? The less time I spend making the report, the more time I can spend thinking about the report, its implications, and what I can recommend for our clients.

Here’s an example of a simple report optimization. We have a series of templates we use for each month’s reports. In those templates, there are placeholders for the month, and typically I copy the report from one month to the next to preserve some historical data, plus any upgrades I’ve made over time.

Yet for dozens of websites and projects, even this can be a bit laborious. Finding the instances of the previous month and updating them to the next month takes time – not a ton of time per report, but it adds up. I could have someone else do that part, but that’s not a good use of their time either. No, the best choice here is to automate this process – it’s important work, but it’s low value work.

In the days before generative AI, I would have spent a few hours writing this code. Today, I simply log into ChatGPT, fire up the GPT-4 model (the current best model for general coding), and ask it how to find and replace text in a directory full of PowerPoint presentations:

Powerpoint Replacer

Boom. The Python script is ready to use. I copy and paste it to my computer, and now I’ve saved about 12 hours per year. Is 12 hours a year a huge deal? No, not really. In the grand scheme of things, it’s relatively small. It’s not going to transform the company and make us instantly more profitable…

… by itself. Here’s the thing about process optimization with AI. It’s not sexy. You’re not going to win any awards for its innovative use. But as with all incremental things, it adds up. Shave 15 minutes here, 30 minutes there, and the savings add up quickly, to the point where suddenly you’re looking at free hours, not free minutes, in a day.

When we first started Trust Insights five years ago, the reporting process took a couple of full days for reports that weren’t super insightful at the time. They were significantly better than what other agencies were producing, to be sure, but looking back on them is like looking back on your Halloween costumes as a kid. They’re cute, you might cringe a little, and you know that what you can do today is so much better than what it was like a little while ago.

You can’t deliver those optimizations if you’re mired in processes that should be done by machines. You can’t improve if you never have time to focus on improvement. Today, the reporting process takes about the same amount of time, but much less time is devoted towards those manual, repetitive, relatively low value tasks and more time is devoted towards the insights, the recommendations, the strategies that good reporting should beget.

The key takeaway here is that AI can be used to save time and dramatically improve the quality of your work product incrementally. You don’t have to – and probably shouldn’t – wholesale replace giant processes with AI-driven processes, especially at the beginning of your AI journey. Instead, look at piloting the use of AI for frequent small wins, small tasks that can add up to big efficiencies in the long run.

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Upcoming Events

Where can you find Trust Insights face-to-face?

  • MarketingProfs B2B Forum, Boston, October 2023
  • Content Jam, October 2023
  • SMPS AEC AI, October 2023
  • DigitalNow, November 2023
  • Social Media Marketing World, San Diego, February 2024

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