Vance Reavie, CEO at JunctionAI talks about the best ways for marketers to use AI to drive more business impact while diving into a few martech and marketing trends in B2B:

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Welcome to this martech chat Vance, tell us more about Junction AI? 

Yes, I’d love to! We created Junction AI to help software platforms, like Amber Engine, take advantage of their massive data opportunity. These platforms have end client data, and end clients increasingly need analytics and insights that help improve their performance. 

The problem is that AI projects are very complex, about ½ never make it past prototyping, and marketing are laggards in adopting.  There are huge shortages of experienced data engineers, data scientists and critically data “translators, people who can assess and align data driven insight opportunities – and critically tell the data story – to support the needs of decision makers, like marketers or ecommerce project managers. 

We also specialize in the unseen/unstructured data, marketers generate more data than anyone and this is the main type. This is the brand and user generated images, text, video etc. This data is all about the audience and the product/service. Insights from this data explain WHY something works, critical for great decisions and reducing risk. This data is the hardest to work with though.

What’s unique about our approach is our platform intelligently automates many of the most complex parts, and our accessible and inclusive data lab approach allows us to work with the platform and their end clients to get exactly the insights they need to drive impactful results. We become partners in the product, with our team engaging to help tell the data story. 

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Can you comment on a few latest digital marketing trends for B2Cs that you’ve been observing closely? 

Some of the key trends I see emerging strongly are the need for more custom fitted platforms and explainability for AI – answering WHY.

The first is simply a recognition that marketers and ecommerce managers, and others, already have many choices of SaaS platforms. But each of these specializes in its own slice of the whole, meaning users are stuck with a complex workflow involving so many moving parts, everything they need to do to change or adopt new technologies means changing how they do work.  It also means that they end up with a disparate bunch of services but there is no unity or ability to benefit holistically. We are now seeing a push back, the need to have more flexibility in SaaS platforms to cater to and customize to an end user’s needs. We’ve adopted an integration first mentality; we integrate our AI driven insights into existing platforms so the information users need is readily available and easily accessible at the point in time they need it most. 

The second is explainability, the ability to answer WHY. There are a lot of AI solutions on the market, but most do not explore the why something has the impact, they can’t explain what it was that made the difference, making it difficult to know what you should be doing or do next time to repeat success. It also means you don’t know what to avoid or what generates risk. Ability to analyze audience interactions to brand and user generated content, the images, copy, videos, reviews, interactions etc, getting into this data is how you understand what triggers interactions and why. It’s not enough to know an ecommerce listing ranks better with a new lifestyle photo, the marketer needs to know what it is in that lifestyle image that captured audience engagement, so they can repeat that success.

How are you seeing AI and predictive engines change the game for end users and marketers today?

It’s all about reducing guesswork. So much of our time in marketing is about discovery and live experimentation. This is all very time consuming, it can take months and typically never ends, but you still don’t know why what worked worked or why what failed failed. 

Marketers generate more data than anyone else now in brands, this is complex unstructured data, its simply not humanly possible for them to manually make assumptions, manually test it on their data. The data is too volumous and human data analytics is too limited, it relies on human assumptions and bias – well and humans! With an AI you can easily scale to rapidly analyze data and discover relationships you might not be aware of at all.  

What are some best practices that you feel marketers should follow when using AI backed platforms to lift digital marketing trends?

Marketers need to recognize that to be best practice in adopting and benefiting from data driven insights they need to better understand how to use data, and they need to focus their attention on using data proactively, bringing the data to the front of the process. Marketers also need to understand their new role is as data story tellers, understanding the business need and understanding the data needed to inform marketing opportunity. This is the WHY data, it’s not another metrics dashboard, we are drowning in dashboards telling us about how something performed. 

For AI to be successful, marketers need to adopt this data storyteller role, they need to understand what generates the insights they need and how to apply them. This is a high value add role, AI can generate predictions, but it takes a human to use judgment for a great decision. We also need to step back and check our own assumptions and biases, and listen to what the data is telling us. This can be challenging, but the role of judgment is far more interesting and strategic.

A few predictions and thoughts on the future impact of AI in martech?

We will increasingly see AI become an “as a service” function within the platforms we already use. While many very large fortune 1000 companies can afford to have their own teams to develop this capability, most don’t. The range of skills needed from devops, data engineers, data scientists, project managers, analysis etc is too much for most, let alone getting experienced and skilled people. Just like cloud hosting transformed that market, AI as a service will allow any organization to rapidly implement and benefit from AI machine learning without having to build out, maintain and support this function internally. Of course you probably know I am going to say this – I think an emerging factor will be the need for marketers to explain why, and at the moment traditional metrics like CTR, conversion rates, etc don’t do that

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Some takeaways for marketing leaders and CMOs/CEOs for the rest of 2021?

CEOs are already demanding their CMOs get a handle on data, understand how to transform their functions with it, and use it to make better decisions that drive revenue growth (and prove it). They will need to show results for the spend, real bottom line impact, and be able to explain WHY. 

Today the competition is not to outspend your competitor, it’s to outsmart them. This is exciting work! While AI may automate a lot of marketing functions, this is going to change the roles and skills needed in marketers. When you can have an AI that can make predictions and insights directly based on your own first party audience data on what they are demanding, features, benefits, colors, packing innovations etc you are rapidly eliminating wasted time and spend, mistargeted marketing. 

This has got to be the most exciting opportunity for any brand, leveraging your own data resources to outsmart your competitors, and building a team that knows how to use the data and do this will define success.