In Otter Words -- Kitty Kolding, Chrysalis Partners

12:03AM Aug 26, 2020

Speakers:

Kitty Kolding

Ross Rubin

Keywords:

data

otter

clients

conversations

kitty

humanizing

calls

chrysalis

kinds

understand

listen

people

appealing

salespeople

studies

monetize

internal

combination

research

sales

Hi, everyone. I'm Ross Rubin, Principal Analyst at Reticle Research. Welcome to another installment of In Otter Words. Our guest today is Kitty Kolding, founder, and CEO of Chrysalis Partners. Kitty has a long history working with data and market research. She was previously the CEO of Infocore, a company that works with consumer data. In her latest initiative, she's working with clients on the idea of humanizing and monetizing data. Kitty, thanks so much for joining us today.

Thank you, Ross. Great to be talking with you.

Why don't we start out by having you explain what humanizing data means?

Sure. At Chrysalis, we do two kinds of things; making complex data easier to understand and consume by people that are not analysts, technologists, or engineers. It's really meant to make sure that everyone gets the benefit of data in a way that they can take in and take action with. That's the idea. The other part of our business is monetizing data, which sometimes interacts with the humanizing side. Sometimes we're helping clients humanize their data, and then once we've done that, we're in a better position to help them monetize it because it's more appealing to certain kinds of buyers. Those are the two kinds of things that we do.

Really interesting. Very often, when we think about data in the enterprise, we think of this firehose or perhaps unfiltered data that makes its way to the business units, and then people working there provide feedback in terms of new rules to implement or feedback to the engineering and development teams about how they want these reports to change. Of course, that assumes that the people receiving the reports understand what they're seeing and understand the relevance to their work.

Right. We care a lot about human-centered design focused on data communications. That's the essence of it. We think about not just visualizing data and putting it into charts and graphs, but a ton of thought about how should that presentation of the data look, and how should it differ depending on whether you're presenting it to technical people or product people or sales or customer service or ops. We do these audience studies to figure that out. We go and talk to internal users or actual customers to understand the nature of those people, how technically adept they are, how comfortable they are with data and analytics. Then we can tune the data presentation to them, which is a combination of visuals and analytical narrative, and then just the overall presentation. We think about things like pre-attentive attributes. We think about the way the human brain processes information because it can make all the difference between someone understanding and someone's eyes just glazing over and moving on. That process where we're doing these audience studies is one of the places where we use Otter the most.

Okay. Let's drill down on that a bit more. In market research, we often talk about quantitative data, numbers, and qualitative data, which is derived by interviews. Those two really seem to come together in the work that you do with clients. Could you give me an example of some application that you use Otter for in combining these kinds of inputs?

There's generally two scenarios where we use Otter. Both of them revolve around this idea of where we are trying to make sure we can free up our mind space in the context of some kind of person-to-person activity so that we can listen and be good conversationalists and understand the context of the conversation without losing any of the detail. That's really the key for us. Sometimes that's in the context of client calls or sales calls, where there's a lot of information passing back and forth, sometimes a lot of jargon and technical references that I might have a little trouble keeping up with anyway. Trying to do it while also writing it down and organizing it and listening and playing back while I'm conversating gets really overwhelming for my brain. So it's my sidecar to handle all that for me so that I can be entirely present. Then, later, I can go back and synthesize that and listen to the audio, read the transcripts, and make sure that I haven't missed some nuances. It's also used when we do that in a training scenario. Sometimes we will capture that data. It's really hard to do a better job of training salespeople than to record a sales call and let them listen to it over and over. Even if they just listen in on one call, it's nowhere near as good as them having a library of sales calls that they can go replay and re-listen to. Again, in that sales conversation, we're training up new salespeople right now on a project and it's become really important to the training side of it.

Has the search capability come in handy at all? The great thing is that you can go across multiple calls.

We're thoughtful about how we organize them. Frankly, we're not even as good as we could be at using some of those features, but just the basic toolset is terrific. Along those lines, we're doing a lot of that work on the phone. Sometimes we don't want to put those calls on speakerphone or whatever. So we have the ACR integration so we'll actually record the call. That integration with Otter works beautifully; just pushes the audio over to Otter and it gets transcribed. That is a huge benefit, too. If we're trying to use headsets or do some other way of handling the conversation, especially now when everything is entirely virtual, it becomes a really useful tool. That's the sales part of it. Then there's the part that we use for these audience studies. On the audience studies side, sometimes they're internal audiences. We're just finishing up a really big project for a client in E urope where we did a whole audience study with all of their internal analysts and BI experts to try to understand what was going on and how things were going. There are some issues; it's a huge company. We did extensive interviews with these folks in conjunction with online surveys. These conversations were lengthy. They were at least an hour apiece, and very technical, very detailed. For me personally, I did a lot of the calls myself. A gain, I needed to free up my mind space to be sure I could engage in those conversations, and remember and go back and replay it, but we also needed to capture the verbatims to put into the study. So we had to have those exactly right and attributed properly. That's one of the things that totally saved us in these projects because it actually becomes part of the report that we deliver. I couldn't be confident that we would get that exactly right without something like Otter.

It sounds like you're actually tapping into a fair number of advanced Otter features: ACR integrations, speaker identification, possibly even the ability to add custom vocabulary words for specialized fields like law, medicine, engineering. As you work with clients, do you ever see opportunities where you think they could benefit from having access to real-time transcription? I imagine, for example, that a lot of the data that you work with comes in the form of customer feedback dialog, for example?

The same issues that we grapple with and that we needed Otter for exist, definitely, in our client organizations. One scenario, again, is their selling activities. A lot of these companies are quite large and there's a ton of complexity in some of these conversations. They need to go back to experts internally to try to replay these conversations and get a response from an internal expert that may have gotten garbled if the salesperson tried to summarize it themselves. So being able to have the exact terminology and context that the customer uses becomes really important. We have been noticing the industry-specific vocabularies popping up. We didn't really realize it until fairly recently. That's really important to us because each of the clients that we work with are such different industries. One of our clients is in the language intelligence business. So they track 7,000 languages around the world and dialects and language families and all this stuff that is an entirely different set of vocabulary that, frankly, I didn't even learn until we had these conversations compared to my other client that I'm talking about here that is in the manufacturing business. The idea of being able to let the system understand those things and track them is really valuable. They're so different that it saves us a ton of brain damage, trying to try to retranslate those things.

That's great. As you think about the future, what kinds of trends do you see on the horizon in terms of your client needs? What kinds of challenges do you think Chrysalis will be able to help them with moving forward?

I've been doing data monetization for a very long time, and Chrysalis was founded on the idea that data better handled can produce better results, whether it's internal value or external results, like making it monetized. I think that at this very moment, given all the insanity going on in the world, and given all the uncertainty with COVID, and all the incredible ramifications that we're only beginning to see of what has happened from this pandemic, the idea of being able to create an incremental revenue stream from an asset you already possess, which is data, which everyone has in absurd abundance, the idea of being able to turn that into something that delivers revenue and value is pretty appealing, I would say perhaps more appealing than ever, given how uncertain everyone's other more traditional revenue streams have been. For us, that seems to be at least the near future is continuing. That work is always a combination of humanizing it, reworking it so that it's incredibly appealing to different types of buyers, and then packaging it and helping them sell it and put it into the hands of these folks. That combination, for us, I wish it had happened at a time that didn't involve a pandemic, but it does seem to be a promising combination of capabilities at the moment and a welcome benefit for customers.

That's interesting that you should mention the pandemic, Kitty. One of the things we're observing in our research, particularly as offices begin to reopen again, is the need to bridge the communication gap between what may be happening in conference rooms in the office and the discussions that are taking place with remote workers. Being able to have good records of what's happening in those conversations seems like a need that's only going to become more important.

Most definitely.

Well, I think that's where we're going to have to wrap up. Kitty, I want to thank you for sharing your insights today on how your clients are working with Chrysalis Partners to humanize and monetize data. If anyone listening would like to find out more about Chrysalis Partners, you can find them on the web at chrysalis.partners. You can follow me on twitter @rossrubin, and you can learn more about how Reticle Research helps clients at reticleresearch.com. Of course, you can always find Otter on the web at otter.ai and download the app from the Apple App Store or Google Play. For In Otter Words, I'm Ross Rubin. Thanks for listening.