Ushering a company through a rebrand is a daunting enough task. Now try walking that tight-rope when your company is pivoting from a non-profit impact-driven organization to a for-profit company focused on making sure its clients receive accurate data to power their A.I. Sounds challenging, right? A.I. has become something of a buzzword in marketing circles, the technology has merits if you understand what it needs to make it successful.
“There is an idea that without that data artificial intelligence wouldn’t exist. There’s synthetic data creation, and there’s now models that can train off of very little data. But at the highest level, A.I. just doesn’t exist without training data. And quite honestly, trading data at this point, doesn’t exist without a massive human workforce. And that workforce is often overlooked.”
Those are the words of Heather Gadonniex, the VP of Marketing and Strategic Partnerships at Sama. She is a marketing and data expert with a mission to deliver actionable data to power marketers’ ambitious A.I. goals. On this episode of Marketing Trends, Heather discusses why marketers need to know where their data is coming from in order to know how to properly use their datasets. She also shares stories on how she helped Sama pivot from a non-profit organization into the world of for-profit business, the challenges of their rebrand and the importance of impact.
- What Matters: There are a few core things that really matter in any business: personnel, culture, revenue and impact. Those four pillars all require different departments being in alignment with each other. Without any kind of alignment between your product teams, marketing teams, or sales stakeholders, you don’t have the ability to grow, scale or make the most impact that an organization can have in the marketplace because you’re not all focused on the same goals.
- Data 101: A.I. will continue to be one of the most important tools moving forward, but marketers must understand not just how to enable those insights to power your business, but where that third party data is coming from. Is the data set that the company is providing trained on your data or is it coming from another data set? The answer to those questions will impact the predictions you receive from your tech stack.
- How to Train Your Data: There’s this notion that A.I. and machine learning are going to replace marketing jobs in the future. However, that is simply not the case. What is often overlooked with new marketing technologies is the training data that goes into these tech stacks. At the highest levels, A.I. doesn’t exist without training data, which does not exist without a physical workforce behind it.
“I fundamentally believe that there are a few core things that really matter in business [and they are] people, culture, revenue and impact. All of those are achieved by having a super strong alignment within an organization — alignment between a product team, a marketing team, a sales team, and delivery ops. Without this alignment, you don’t have the ability to grow, scale or make the most impact that an organization could have in the marketplace. I do think that this alignment is only really realized when everyone is rallied around a clear, inspiring vision and actionable strategy.”
“Those early days of our marketing program we really focused around building out this for-profit brand and building out the brand that represented more of a robust and value-driven picture of our technology and how that technology fundamentally helped organizations succeed, and putting that technology first and foremost.”
“I’ve started to think about the [consumer persona] a little bit as a double funnel. You have your buyer persona and your user persona, and that user persona often overlaps with the buyer persona. Now we’re building out an approach to ensure that we have a community built with the user persona and that community is first and foremost, the most important thing to focus on with a technical product. With the buyer persona, we’re continuing on with more of an ABM value-driven marketing.”
“We find that [brand] impact is really the sticky sauce. It’s what gets people hooked to the brand. It’s what gets people hooked on the core mission of the organization and it really is what allows us to retain and maintain our super high retention rates, customer satisfaction rates, and resonate and connect with customers in a really deep and meaningful way.”
“Without delivery on our core value proposition of providing training data that fuels accurate A.I., that impact mission, it’s not meaningless, but it’s not the primary driver and not the primary purchasing decision.”
“Model vigilance is a brilliant term. That’s the concept of ensuring that when your model is in the wild, when it’s actually being used into the war of the world, you’re constantly monitoring it to make sure that it continues to work as intended. If there’s some component that’s not, then you again go in and feed more data and retrain.”
“When you think of artificial intelligence and you really understand how it’s created, there is an idea that without that data artificial intelligence wouldn’t exist. There’s synthetic data creation, and there’s now models that can train off of very little data. But at the highest level, A.I. just doesn’t exist without training data. And quite honestly, training data, at this point, doesn’t exist without a massive human workforce. And that workforce is often overlooked.”
Heather Gadonniex is the VP of Marketing and Strategic Partnership at Samas. Heather is passionate about bringing world-changing technologies to market and using supply chain purchasing power for good. She is a data-driven strategist experienced in developing and leading go-to-market, communications, and sustainability initiatives at start-ups and multi-national organizations. Heather is most happy when she’s growing companies that make a positive impact, enjoying the outdoors, and spending time with her family.
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