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Lee McCance, Chief Product Officer at Adverity chats about the evolution of analytics tools within martech in this catch-up with MarTechSeries:
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Hi Lee, take us through your journey as a product visionary in SaaS over the years.
I’ve been involved in marketing since the beginning of my career, joining Yellow Pages straight after university, helping them automate and improve the system advertisers used for booking ads. At the time, Yellow Pages was still just a thick paper book, so you can imagine how long ago that was!
I’ve worked across the technology industry in security and gaming, then more recently I’ve been back in the marketing and adtech space with Essence, GroupM and Choreograph. My focus has always been on solving user and customer problems, and how we can take advantage of new innovations and technologies to change ways of working for the better.
I’ve always worked at large organizations, so I’ve faced my fair share of challenges in building platforms that serve diverse groups of customers at scale, across different markets. Unsurprisingly, it’s always a balancing act – making sure you meet the needs of individual markets and customers while aligning a more global perspective.
What immediate plans do you have for Adverity and how are you planning to shape the product’s development?
Adverity’s offering is very much grounded in the value that we bring customers today and being mindful of the partnerships we’ve built. We will make sure we remain best-in-class in terms of enabling customers to build a complete and trusted data foundation so their data is ready for analysis.
But when it comes to technology, staying static is a surefire way to fall behind. So we’re also launching some interesting things from a conversational and agentic AI perspective to help them get faster insights, improve efficiency and collaborate easier– again, it’s a balance of continuing to do what we’ve always done and taking advantage of new technology where it is relevant. We want our customers to recognise that we lead the industry in data for marketing, while also innovating to help them solve new problems and evolve with their needs.
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How are marketing and analytics tools today within the martech ecospace evolving?
There are a number of different trends impacting the way marketing and analytics tools are evolving. One of the key areas is the focus on how AI will change the way people interact with their data. While it’s premature to say that dashboards and Business Intelligence (BI) tools will disappear completely, we’re already seeing tools like conversational AI are transforming how teams engage with their data – fewer dependencies, more self-sufficient teams and faster insights.
Our job is to work out how these tools fit in with the workflows and processes that our customers are familiar with and that they’re using on a daily basis. There’s a huge opportunity to continue to provide industry leading data connectivity and harmonization, but also help end users take advantage of all the great benefits of conversational analytics tools.
But we also have to remember that people won’t adopt new approaches if they don’t trust the data underneath it. We’ve put a lot of focus on making sure there is real transparency in terms of the way our platform works; it’s not a black box and users can see the reasoning and the logic behind the answers.
A few thoughts on the growing impact of AI on martech and marketing?
One of the key things that we need to get right with AI is to help people be more effective in their jobs. If tools are difficult to use or require marketers to learn specific skills then that’s counter-productive. They need to be intuitive and have natural interfaces, allowing marketers to uncover insights quickly and easily.
At the end of the day, marketers’ expertise lies in creating and executing on strategies for their brands, their customers, their product lines, and their markets. AI needs to be a strong partner that supports them so they can continue to focus on what they’re good at, rather than demanding they adopt new processes.
As marketing tools evolve, what skills should modern marketers focus on developing?
One of the biggest challenges our customers have is the skillset of their users being limited by their data maturity and capabilities. New tools and products can go a long way, but we want to encourage data literacy and that’s not just about being comfortable with big data at scale, but doing it in a way that’s compliant. Much of the data our customers are working with is very sensitive and it’s very easy to let unconscious biases slip through or to apply data in a way that isn’t appropriate.
If you look at the way people are interacting with technology generally, most people are already using conversational AI, so our interface needs to support that instead of forcing them to do something that they’re not comfortable with. By the same token, we don’t want to stop them working with the tools that they’re already using and familiar with, so we have to work out how we can complement their existing processes with powerful products and tools.
How can marketers fix ongoing issues around data management and the need for high-quality data?
One common problem we see across businesses is that data exists within separate silos across the organization. Different departments have built their own data structures that don’t relate to each other, and critical information can be buried away in spreadsheets, presentations, emails and messaging platforms.
For marketers to extract full value from their organization’s data, they need to have a solid data foundation in place. High-quality, trustworthy data is essential to get the most from AI tools. Data (structured and unstructured) needs to be connected and unified to ensure consistency and accuracy before it is ready for analysis. Fixing issues around data management might be laborious, but it’s absolutely necessary for the marketing department – and the wider organization – to fully realize the value of its data.
Three takeaways you’d share with product teams looking to build and implement new features as part of their offering in 2025.
It’s vital that they start with the end user in mind. They must think about what the end user is doing day-to-day, how they can make their data useful and usable, and how to make their jobs easier.
Product teams also need to ensure that customers and users can trust the data and intelligence they’re getting. There has to be a great deal of transparency and traceability in the reasoning, otherwise they won’t believe what they’re being told.
And my final piece of advice: remain curious. This means not just staying up-to-date with how the martech and marketing industries are evolving in terms of data, but also how other sectors are changing their approach to data and how this all feeds back into your own team’s products and offerings.
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About AdverityAbout LeeAbout Adverity
Adverity is an integrated data platform for connecting, managing, and using your data at scale.
About Lee
Lee McCance, is Chief Product Officer at Adverity
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