It’s a very exciting time for AI. Innovation is happening at breakneck speed. Each week brings new developments, whether it’s about the large language models (LLMs) themselves and how they’re becoming more performant and less expensive or an announcement on content creation across video images and text.
When I prompted Williams about the market trends and dynamics that are arising, propelling AI forward, he says, “The main trends we’re seeing are that customers need a lot of personalization at scale due to the continued proliferation of digital touch points. And at the same time, as those digital touch points proliferate, there’s also an increased focus on return on investment (ROI) from marketing due to rising advertising prices and macroeconomic pressure on P&Ls.
“So customers are evaluating how to leverage Gen AI across a broad range of use cases for advertising and marketing, which include creative and content development, enhancing customer journeys, personalizing advertising, and marketing experiences, understanding customer sentiment and optimizing operations. Enabling those highly personalized experiences for each customer will, in turn, help increase engagement and loyalty, and then obviously, drive ROI as a result.”
Everything he mentioned completely resonates with our experience at Amperity too. We’ve seen so much growth in eCommerce over the last several years. It’s growing 15 percent year-over-year, and marketers have always known what personalized experiences should look like in the age of brick and mortar.
There are many great examples of personalized experiences – the challenge is, how do you actually deliver personalization at scale and to William’s point, in a way that’s efficient and cost-effective?
Generative AI makes much of that a reality. It drives the cost of content creation to zero, which enables brands to speak to their customers in a more one-to-one manner across all of the different digital touchpoints.
AI as a marketing assistant
Williams shares where Gen AI is shining as a marketing assistant, of sorts. “Amazon Q is a new type of generative AI-powered assistant that can be used specifically for work to be tailored to your business to have conversations, solve problems, or generate content. It uses the data and expertise found in your company’s information repositories, such as codebases and enterprise systems.
“You could use Q, for example, to:
- Learn a brand style guide, then
- Use that information to turn a press release into a blog post that adheres to those standards, then
- Analyze how a brand has shown up on social media, then
- Create new posts around those releases that will make sense to followers, then
- Analyze the results of those posts, and finally
- Summarise them for review for teams
“It’s almost like this self-fulfilling circle of incremental productivity that’s happening as a result of leveraging some of the generative AI capabilities that come to use as a result of a bot but are plugged into the systems and data that your enterprise organization owns.
We’re only in the very early stages of that, which is pretty exciting.”
At Amperity, we work with many customers who want to be more data-driven and customer-centric. We know that comes down to an understanding of the customer – even figuring out what the key segments are that you should be going after and what types of campaigns you should be launching.
If you think about the analysis you have to do to answer those questions today, there are so many barriers you must understand, including:
- Your underlying data and the schema
- SQL
- How to build visualizations
There are many barriers to a user from the customer data to actually figuring out what strategy should be launched. We’re seeing a lot of folks throw Amperity into the mix here too, developing tools where that data can be more democratized. You can ask questions about the data with natural language as opposed to needing to write SQL. This will lead to a lot more data-driven decision-making as folks can more easily access their data relative to the mini barriers that were in place previously.
Key Takeaways: Setting your brand up for success with Gen AI
In the journey of crafting a Generative AI strategy, Williams points out five key elements that play a pivotal role in ensuring success.
They are:
- Tech stack: Your tech stack is vital. You should have the ability to explore models, test use cases and choose the right ones.
- A solid, mature first-party data foundation: Generative AI relies on the data to function properly, which means you must have robust data ingestion storage and management capabilities to make sure that the first-party data is accurate and as close to real-time as possible to provide accuracy in the model outputs.
- Human oversight: You still need that human-in-the-loop intervention to make sure that what you thought was going to happen is happening and that there are no anomalies.
- AI-specific analysis skills: Leveraging AI requires the ability to interpret and accurately apply AI model outputs. You must ensure that your teams have the expertise to understand how the tools work and how best to put the data to work.
- Process redesign: Consider existing processes or workflows that need to be resigned to take advantage of General AI.
Amperity delivers the data confidence brands need to unlock growth by truly knowing their customers. With Amperity, brands can build a unified customer profile foundation powered by first-party data to fuel customer acquisition and retention, personalize experiences that build loyalty, and manage privacy compliance. Using patented AI and machine learning methods, Amperity stitches together all customer interactions to build a unified view that seamlessly connects to marketing and technology tools.
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