In marketing, there’s always a shiny new object to admire, whether it’s a (supposedly) smarter algorithm or a platform promising effortless performance.
But the fundamentals always still matter more than whatever’s trending, says Sharona Sankar-King, chief data and product officer at Havas Media Network, North America, on this week’s episode of AdExchanger Talks.
Driving profitable growth and market share “comes from a solid understanding of the customer,” Sankar-King says, and from “being very well aligned in your data strategy.”
“It still really baffles me that there are so many organizations chasing the shiny things and skipping over some of the fundamentals that drive success,” she says.
For example, instead of hoarding every possible scrap of customer data just because it’s there – or in the hope that AI will sort it out later – it makes more sense to only collect the data you actually need to answer a specific question or achieve a particular outcome.
“As a data scientist,” Sankar-King says, “one of the very first things we always look at is garbage in, garbage out.”
Data is either “fit for purpose,” she says, or who needs it?
“There’s a lot of data that can be useful for nothing,” she adds, “and there’s some data that is extraordinarily useful in finding those treasures of gold” that drive business results.
These fundamentals extend beyond data and into workflows. Sankar-King is less impressed by any single AI feature than by whether a brand or agency has done the unglamorous but critical work of aligning leaders, agreeing on KPIs and developing an approach that connects intelligence, planning, activation and measurement.
“Just because an AI serves something up to you doesn’t mean it’s the right thing to do,” she says. “Our team still have to be analysts. They still have to be scientists. They still have to be critical thinkers – and they still have to understand the levers that drive success.”
Also in this episode: Transparency as a competitive differentiator, pushing back against black-box platforms, why Havas built its own AI operating system and where causal AI fits into the post-MMM measurement tool kit.
