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Data-Driven AI is the future of customer experience, François Ajenstat told us at a recent interview. François is Chief Product Officer at Amplitude, the company behind a digital analytics platform aimed at helping B2B and B2C businesses build better products, websites and ecommerce experiences through behavioural data. François stressed the significance of data-driven AI within analytics but also delivered a clear warning: Don’t fall in love with what you have built! Focus on delivering second-to-none customer experiences instead. He emphasised that implementing chatbots without purpose isn’t beneficial, noting that too often, in this new world, businesses rush to add chatbots but it doesn’t make “anybody happier. No. People are still frustrated.”

Data-Driven AI Is the Future of Customer Experience

AI Integration and Implementation in analytics, what does it mean?

François Ajenstat. While AI capabilities have existed for years through statistics and machine learning, generative AI has opened new possibilities. We’ve integrated this through “Ask Amplitude,” allowing natural language queries with visual responses. Thus, users can simply ask questions about their most engaged users and receive actionable insights.

I could ask the system, “Who are my favourite readers, for instance?”

Absolutely. And you’d get the answer in a flash and the system would suggest what actions you should take and how you should engage them. Alternatively, it could help you visualise the journey of those users.

This is what you call the 3 key aspects of Data-driven AI Implementation

F.A. Indeed, we focus on three different areas with a massive potential impact.

1. Simplification first: removing complexity through natural language interfaces. We’ve had speech-to-text capabilities for years, but users often found this feature intimidating. There used to be a learning curve before you could use it properly. Now it’s a lot easier. You just ask a question in natural language and it brings the result for you automatically.
2. Augmentation is the second area: it’s about enhancing human capabilities rather than replacing them. A great example of that might be if you’re analysing some data and you want to understand the outliers* or what the key drivers are. Help me understand the root cause of this problem. This is where you can unleash AI to really drill into the data on your behalf and come up with insights. So we’ve added those capabilities in our product. We’ve also added what we call a data assistant, which will tell you automatically where there are data quality issues or improvements.
3. Last comes AutomationMarketing automation in B2B enables marketing processes to be managed automatically across multiple channels. With marketing automation, companies can target their visitors with automated messages via e-mail, the web, social networks and SMS. Marketing Automation in B2B Above is a diagram explaining how the scenarios work in marketing automation, based on behavioural scoring and profiles. Messages are sent automatically, according to sets of instructions called workflows. The Limits of B2B Marketing Automation Some companies install marketing automation mechanisms while their maturity on the subject is ‘under construction’. They deploy technology for technology’s sake which leads them to use tools that: this is where you find workflows and you ask AI to execute tasks on your behalf. It could be about automatically engaging users. It could be around guiding those users by delivering the right content, images, text, based on given use cases. Enabling 24/7 execution of routine tasks while allowing marketers to focus on strategy. The key thing is to engage the user at every single touch point and use AI to make every interaction a little better so you can drive a better outcome.

*Outliers (statistics): a data point on a graph or in a set of results that is very much bigger or smaller than the next nearest data point.

Do you think that AI is made for beginners or super experts like Steve Yegge?

F.A. Every time new technologies emerge, it causes fear, uncertainty, and doubt about the jobs that are going to be eliminated.

Think of word processing. In the 50s and 60s, the only people who would type were office secretaries. That was a specialised job. When WordPerfect and Word came out to the marketMarket definition in B2B and B2C - The very notion of "market" is at the heart of any marketing approach. A market can be defined..., that job got removed. But at the same time, it empowered millions and millions of other people to be able to perform new tasks by themselves. And that was extremely liberating.

It doesn’t eliminate the fact that some people are good writers and some people are not. You still need the core skills to know how to write properly.

And I think that in our jobs, whether you’re in marketing, engineering or product management, you still need to grasp the fundamentals to understand what is happening. But you can eliminate some of the more basic work and spend more time on the higher level.

Yet, Focusing on the Higher Level Requires Skills

F.A. Indeed, it does. Think of these new programming languages where you don’t have to learn all the basic hard-coded engineering. You are therefore facing a higher level of abstraction. The same goes with AI. It is merely providing a higher level of abstraction. It makes it possible for you to focus on building greater software versus knowing all the mechanics below it.

Will AI become a staple of user experience?

F.A. AI will become a core capability in all software, driving faster innovation and creativity. The focus on user experience becomes even more critical as expectations rise. Success depends on delivering value to users, regardless of the interface or platform.

User expectations are going to grow. And we will all have to compete more effectively or more aggressively on winning the rights to be able to serve those users.

I think that changes the equation a lot. We now have a higher responsibility to deliver better quality experiences.

But the core of all these experiences is data. We have to be able to collect more and more data to understand what’s working and what’s not working.

Just delivering a chat experience on a website doesn’t mean it’s a good experience.

Too often, in this new world, businesses rushed to add chatbots. Is anybody happier? No. People are still frustrated. But the real question now is “how do you continuously use that data to deliver better experiences?” To better understand your funnels and user journeys and drive customer retention.

Where is user experience headed in the future?

That’s the $300-million question. If your website experience is clearly positioned but you are delivering your chat capability through a third-party interface, how do you actually differentiate?

All that matters is how much value you are delivering to your users.

Don’t fall in love with what you have built. Fall in love with your customers and this should guide you every single day.

Could we imagine, in a not-so-distant future, self-programming software?

F.A. Users want software that’s adaptable, continuously monitoring itself to drive the right outcomes. I think one of the keys to achieving that is the ability to express the metrics, the goals that you have. Because the software will never know what ‘improvement’ means.

Thus, if you were to say, ‘My goal is to increase signup conversions,’ then the software could look at the data and improve itself, change terms, add new buttons and new capabilities that will drive that outcome for you.

I think the world actually is shifting from websites to metrics and outcomes.

And that’s how AI can come through. There’s a lot of gibberish that comes out of AI because it doesn’t know your intent. It doesn’t know your domain. But if you’re able to start with the intent, then everything else makes a lot more sense.

We have a project in development right now where we analyse all the sessions on a given website. We’ll create screen recordings of everything. And from that, we will be able to infer which industry you’re in, where users are frustrated, how users are navigating your site. From that you can start ask AI to suggest changes for you.

The whole online world is going to change, is it not?

F.A. We’re at an exciting inflection point, like the PC revolution or mobile transformation. AI is going to be a whole new world, but we’re in the very early days. And now’s the time to start dreaming, trying, experimenting.

My advice to everybody is to lean in. Don’t be afraid of it. Be the first ones to try and fail and test and really dream of what’s possible because there are incredible opportunities ahead of us.

Those who don’t adapt risk being disrupted by those who do.