Join Tessa Burg for this episode as she highlights the exclusive data that businesses have that sets them apart. Learn how marketers can harness this data to excel through personalization, prediction and pattern identification, gaining a competitive edge that’s uniquely human.
Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. For feedback and marketing questions for future episodes, message Tessa on LinkedIn.
Watch the Live Recording
Full Episode Transcripts
Hello, and welcome to another episode of Leader Generation brought to you by Mod Op. I’m your host, Tessa Burg, and today we’re going to do another Mod Op Minutes. So in under six minutes, we are going to dive into what your business has that ChatGPT does not.
We’ve been getting a lot of feedback from SEO folks and content marketers who are really worried about what’s next for their careers and for their businesses’ websites and overall how they engage and retain their customers. So let’s get into this.
We have some very valuable information and data and content as businesses and marketers that ChatGPT was not trained on, does not have access to. I know that a lot of people listening come from various business types, so I’m going to give some examples that I think go across many different types of businesses and agencies.
First, past purchase history. You know what your customers bought, you know what version or type they’re on, you know what level of service they get, where they are, their location, the product lifecycle, their industry. What are the most common applications within that industry for your product or service. All of this, their past purchase history.
Number two, you have their feedback. You have, this is what I call explicit input. You know what they love about your product. Maybe you’ve done some customer satisfaction surveys. You know why people leave. Maybe you have an off-boarding process where your customer service team captures that feedback. You also probably regularly are getting what they want, so what more do they want to see from your service or product they don’t have today? What are their expectations? That’s number two, customer feedback.
Number three is behavioral data. This is the implicit inputs. So if you have a CDP, you have a great central location for all the ways you communicate with them, how you acquire them. If you don’t, then look at, you know, what are some ways you can enhance the customer record with that information, but you likely do have how you engage and nurture them. And this is just gonna be in your marketing automation or email platform. What type of subject lines do they respond to? Where are they clicking through to? What have been the results of some of your A/B or multivariate testing?
So there are three things, past purchase history, feedback, and behavioral data. Now, what can you do with that?
Well, when you pair this with large language models you can personalize your content, whether that is in a community or in an email. You’re giving them what they want when they need it.
Number two, you can predict. You know product lifecycle management. You might want to get some more data from your ops teams and say, “What’s next for this product? What’s that next feature? What’s the likelihood that these features, maybe in test markets, have already begun to solve this problem for this customer type?”
You can also identify patterns. That’s number three. How well is a certain customer segment doing compared to other segments in other industries? Why? Only humans can jump into that why. Predictive AI and predictive analytics can give us the patterns, they can give us the insights, but we have to interpret what to do with those insights. And how awesome is it when you see where you fall in comparison to others, especially when it comes to business? How is my business doing compared to like businesses?
So those are the three things that you can do when you take your own data, the data you have that ChatGPT doesn’t, and pair it with an LLM, you can personalize the experience, you can predict what’s going to happen with that customer’s product or service before it happens and be proactive about giving them solutions and tools, and number three, you can identify patterns for them, letting them know where they stand, what’s happening in their space, and what point in their product lifecycle are they at in comparison to others with similar applications.
All of these are amazing answers that only your company can give and can really start to be the base for a community for sharing ideas and collecting more of that implicit behavior that allows you to sort of feed that flywheel of content development that is non-commoditized and generated in a creative means that provides actual value.
And we talked about community last time. I still think that is an amazing solution to replace what really was probably low-quality content, commoditized content for SEO anyway. When you try and rank for the most commonly asked question, you’re competing against a bunch of other people also trying to answer that same question. Here you are giving your customers something they don’t get today: a little peek into a crystal ball of what’s going to happen and what you can do for them to help them manage and scale their business.
So I hope that you found that helpful, personalize, predict, and provide patterns of use to your customers, and that will help increase retention, maybe give you some additional avenues for revenue as you start to monetize that content, or link some models together that become a subscription service of your own.
And tune in next time. We’re going to continue this conversation around the impact of generative AI on marketing, and we love more feedback. And thanks to everyone who submitted a question and idea last episode.
Chief Technology Officer & Host of Leader Generation | Mod Op
Tessa Burg is the Chief Technology Officer and Host of the Leader Generation podcast at Mod Op. She’s been leading data-driven marketing and technology teams for 15+ years on both the agency and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa has deep skills in data and tech architecture, software product development and management, digital transformation and strategy. As CTO, she oversees Mod Op’s technology stack to ensure the agency is leveraging and securing the right platforms and data to deliver valuable and measurable results across physical, digital and virtual experiences.