Robert Goldberg

Otter Products

Robert Goldberg is a Senior Consumer Insights Manager at Otter Products (the smartphone case company). 


When you think about insights and research, how do they play into your role? What types of research and insights are you tapping? 

It comes in a couple of different ways.

Number one, innovation. You're constantly trying to create a new product that's going to appeal to a new marketing segment. We do a lot of segmentation research to make sure that our products as we innovate them are targeted to the right consumer. That's been our traditional focus on things. 

Now, it's a little bit less about the product that you develop as it is about the story that you tell with the product. So now our focus is marketing. How do we tell the right story, now that we feel like we have the right products?


What ingredients go into that? What types of insights are you mining to make sure it all comes together into a strong story? 

We're lucky enough as a brand to have really strong awareness in the industry. That's not always the case. If you're an insurgent brand, you need to create poppy awareness, guerilla marketing. 

We happen to have really strong brand awareness. We happen to have really strong brand equity. We're known for quality. We're known for trust. 

What we have to work on now is relevance. When you've been in the industry for a while, you can kind of age out and you need to refresh your brand to be relevant to your newer consumers. That's the name of the game right now for us: relevance. 


When you think about the different types of resources you might leverage to stay relevant or understand your consumers, there's primary qual, primary quant, secondary, internal data… Can you take me through on a high level the stack that you leverage? 

Absolutely. I just mentioned our segmentation. That was step number one. Typically you might do a new segmentation study every five to seven years or whatever is appropriate as the market changes. 

Now that we have a good idea of who our target consumer is going to be, and that was all done through very rigorous, quantitative work and cluster analysis, but now we need to really flesh them out as humans. 

And that's going to be our qualitative deep dives. Let's bring them to life. Let's illuminate this target consumer. It's great to give them a name, to give them an age, but what do they think? What do they look like? Where do they live? Where do they shop? How do they walk? What do their pillows look like?

So it's a lot of ethnography and it's a lot of just discussions and really just empathy. Who are you? We want to get to know you.  


To what extent do you leverage desk research, publicly available information in any of these efforts? 

Very relevant when we were working in tangential categories.

So when you have such a strong brand name, you think to yourself, “Hey, we're in cases. Can we be in screen protection? Can we be in gaming? Can we be in outdoors?” 

And every time you do that, you want to ask yourself, “What's the market opportunity? What does that market look like?” Right from the ground up, you have to start asking yourself competitive analysis. What are some of the white papers with some of the syndicated data that's out there to help me understand this new category that we're going into? That's typically where we find ourselves just sitting at the desk and pulling in all of that relevant information, whatever is available. 


So sort of a starting point for the “known known” corpus of information out there.

Absolutely. You just say to yourself: “Okay, I don't know anything. I'm an open book. Talk to me about what's available. What can I learn?”


When you think of Google, LLMs now, and the different ways you can collect that corpus of publicly available information, what's one word that comes to mind in terms of how well they satisfy or make it easy for you to do that work?

I avoid it at all costs. I don't want to do it. I think it’s frustrating. It's like a homework assignment that you just leave off and you leave off and you leave off and you hope whoever asked you for it just forgets. 

A lot of that has to do with: “is it relevant to my question?” 90% of the time it's not, but you have to go through each one. What date was it published? Is it really answering the question that I was looking for? You find that one really great thing, but it's like about six hours for that one report. You get so excited. So yeah, it’s frustrating. 


Last question for you. It's been about five minutes since we've mentioned this word, but when you think about AI and research, what's your temperature on the potential it might have? 

It's a really great question. Now that I think about it in context to the conversation that we're having right now, I would think it'd be a huge help to refine my requests.

The problem with a new category is you don't know what questions to ask. 

So maybe having some kind of assistant to query you over and over and over again might help you to get to the most relevant information quicker like a real assistant. That could be very helpful. 


Interesting. Thank you so much for the insights!