Videos
AI Accelerates Scale, Content, and Collaboration at Newell Brands
Insights
- Moving AI from pilots into production systems with measurable results is now the main expectation leadership places on marketing and eCommerce teams.
- Efficiency gains from AI are easy to measure, while attributing top-line revenue to AI requires measurement models that most companies are still building.
- Shifting from individual AI tool use to shared, multiplayer workflows lets teams and agents work as one unit and removes the offline handoffs that slow execution.
How can a consumer products company move AI from successful pilots to production systems that grow revenue?
Tambi Younes, Vice President of eCommerce at Newell Brands, shares how the company is putting AI into production across its brands and measuring its impact on the business.
Tambi highlights three critical shifts:
- How pressure on marketing has moved from proving AI in siloed pilots to delivering production-ready applications and agents with measurable results
- Why a CEO mandate to source two-thirds of AI value from consumer-facing revenue is pushing teams to solve attribution beyond efficiency metrics
- How multiplayer workflows let teams and agents collaborate in one place, removing the delays that come with passing outputs back and forth
Tambi describes the speed at which AI tools have become enterprise ready as the biggest surprise, with solutions moving out of proofs of concept and into the way Newell Brands goes to market. Digital content offers an early proof point, where the team has ramped up production without reducing headcount and now has capacity to plan for next-generation content. Tambi also identifies two problems still waiting for AI to solve: faster media mix modeling to guide media investment, and real-time personalization that reaches each consumer with the right messaging in the channels where they shop. This perspective offers marketers a practical view of how productionized AI frees teams to spend more time on strategy and collaboration.
This interview was recorded at the Infosys Aster CMO-CIO Leadership Forum in New York City as part of a partnership between Infosys Aster and the Association of National Advertisers. Click to learn more about the ANA and the Global CMO Growth Council.
Dylan Cosper:
I am Dylan Cosper, and we are here at the Infosys Aster CMO-CIO Leadership Forum. I'm joined today by Tambi Younes, the VP of eCommerce at Newell Brands. Welcome, Tambi.
Tambi Younes:
Thank you for having me.
Dylan Cosper:
The marketing function has always been under a lot of pressure. It's always do more with less. Now I think it's do more with less and do it way faster than you were ever doing it before. What is some of the pressure and change that you have seen within the marketing function in the last six to twelve months?
Tambi Younes:
I think the pressure and expectation is around the scalability of what we're building, and that pressure to get it out into production and get it to market. So we're moving from POCs to these really solid productionized applications and agents that are meant to impact the way that our brands are seen across the marketplace and how we go to market. And so there's been more pressure to establish value and not just show that we can run through a successful POC or a pilot within a silo, but really productionize what we're working on and get some measurable results out of it.
Dylan Cosper:
What kind of measurable value are you seeing with AI beyond the lower-hanging fruit?
Tambi Younes:
I think we started like most folks, targeting internal efficiency. So what time savings can we capture? What cost savings can we capture? But our CEO has kind of laid out a really strong mandate that we want two-thirds of our value to be in consumer facing top line revenue. And we still want to focus on being more efficient and doing our jobs better, but we have to start to shift that to how do we add value to our business and to our brands. And so we are really good, it's a lot easier to understand how you're being more efficient and the cost savings that you're driving. The attribution at market is what we're trying to tackle right now, and so we've talked to a lot of different partners and done a lot of work internally to understand how we measure that a bit better. And so that's an ongoing process for us. But certain things we know are the right things to do, and we'll move forward knowing that there'll be limited visibility into results and attribution in the short term. But we know that we need to be moving forward and building those models as we do that.
Dylan Cosper:
So recognizing that there's maybe a curtain over it right now, but we're working towards more transparency there.
Tambi Younes:
It seems like everyone's trying to figure that out. And there are different levels in which you gain really clear understanding. So we can see, for instance, when we start to push content to market, we know what more content can do for an item or better content can do. We can kind of measure the before and after. But the attribution in terms of how AI factors into that and what value you're driving from AI specifically is where you have to try to build that bridge, which is what we're trying to figure out as well.
Dylan Cosper:
Where has AI surprised you compared to those original expectations that you had?
Tambi Younes:
I think it's the expectations for us in terms of our ability to move really quickly. I think what surprised me the most is the amount of change and the speed at which it's happened. It was already moving really fast, but us being able to get to the results that we're looking for in a very short amount of time, and having them be kind of enterprise ready. So moving out of those POCs and into these solutions that we're feeling really strongly can impact the way that we go to market. So I know it's kind of strange to say at the pace that it's moving, but at an enterprise level and really incorporating those tools within large enterprises like ours has been a pleasant surprise to me.
Dylan Cosper:
So looking at strategy, where do you see a gap currently in AI strategy and the actual execution?
Tambi Younes:
I think what we're seeing right now, and the shift is starting to happen, is strategically maybe we're there in terms of what we know we want to do. So we want to start to string together workflows and bring teams together with AI tools. I think executionally it's been difficult, and I think that's what we're trying to work towards. Staying close with the technology, obviously, it moves fast and we'll get there, and certain firms are getting there. So I think that's where we want to go. I think this concept of single player, folks using tools and building them on their own, and this idea of moving to multiplayer, which has become more of a common theme now, of getting agents and AI tools in the hands of teams and letting them interact as one unit as opposed to me working on something that's really interesting, but then I have to send that output to you offline. And that then again is like a process there, and we want to make it more efficient. So I think that's probably why I think it's the most relevant in terms of where we have a gap.
Dylan Cosper:
As AI adoption matures, what do you think is going to stay the same in marketing?
Tambi Younes:
It's interesting. I think the collaboration across teams still remains. The tools make us more efficient, but honestly, the idea of using AI tools to make the work more efficient allows us to spend more time together as teams strategically trying to figure out where we want to go next. So that remains. The folks that need to be in those seats to strategize, to collaborate, to understand where we need to go to move the business forward, I think that remains and only gets stronger with the ability to use AI to execute and work on the tactical part of the business. There's so much that we've wanted to do, and this unlocks that capacity and the potential. So we've talked a lot about the progress we made within digital content as an example, where we've ramped up our content production without reducing headcount. We're just able to do more with the resources that we have and think ahead around like, what does next-gen content look like, and how should we be planning for the future?
Dylan Cosper:
If you could point AI at one marketing problem and solve it today, what would be that problem?
Tambi Younes:
This is not entirely within my wheelhouse, but I think media attribution and mix, which I think is happening through media mix models. But I think being able to accelerate that process, make better decisions with the amount of money that goes into the media investments that we make, I think would unlock a lot of value for us and a lot of learnings at a faster pace.
Dylan Cosper:
What is an aspect of AI in marketing, or really in your case, in eCommerce, that isn't being addressed today, but you really think should be?
Tambi Younes:
I think for us, where we're not at today, I think we're still focused on the processes, and the go to market side hasn't necessarily made its way all the way to the end consumer. So this idea of real-time personalization, understanding your consumers at a channel level, understanding how to activate at that level, I think we're not quite there yet. We're working towards it and making our way there. But really getting to that individual level understanding of our consumers, where they're shopping, the right messaging, the content to meet them there, the right media vehicles to get there, kind of stitching all of that together would be an area that I don't think has been unlocked yet. But I would assume we would get there based off of the work that's happening now.
Dylan Cosper:
Well, Tambi, thank you so much for the time today. I've appreciated your perspective and insights.
Tambi Younes:
Thank you so much for having me.
