VoiceBase, is a company that offers award-winning voice analytics product power solutions for today’s data-driven enterprises. Using AI, NLP, and Machine-Learning, their solutions unlock actionable intelligence to propel organizations towards success. Walter Bachtiger founded VoiceBase in 2010, with the idea of creating widespread access to spoken information, everywhere. With a data mining and economics background studies, he understands perfectly the added-value of embedded analytics feature in his product.
Can you please describe the value proposition of your company and how do you provide analytics to your customers today?
VoiceBase help brings the vision to voice, and empower organizations with insight from conversational interactions. As Companies have a lot of interaction with customers, they want to know what customers might see want, love, have, like, and what good experiences they’re having or not.
The core VoiceBase technology :
- is an AI which is both voice transcription/analysis of the feelings from data
- push recommendations related to the data and insight thanks to AI
- transforms voice into a vision
Why offering analytics feature embedded in your software was critical for your value proposition?
VoiceBase started with a simple use voice as a thing but “Voice” is hard, and even though customers have voice interaction, it needed to be converted into text. Plus once you have data extracted, the next customers’ question is “tell me what to do”, fortunately, AI bridges the gap between data & actionable recommendations. That’s key.
Then, keeping in mind that everything you do in B2B comes down to ROI, the stake was and still is “selling more, spend less and help their customers”
When we speak of which are the drivers of building analytics, we can enumerate them as technical cooking recipes to get it. Ready?
- after building the technology, you need to make sure the data is clean as good ingredients before cooking your meal
- the API and people would cook on their own
- take control of this cooking and go beyond what they could do on their own and on an automated way
Next, what does mean the impact of offering this packaged analytics experience?
Simple, if you sell the ingredients, you get less margin, the full recipe is a higher margin there is no question about that, but it’s more complicated and specialized. So, like a restaurant, you have to prepare a meal for each table. You make more money to sell meals rather than ingredients.
Obviously, I am closer to proving the ROI, if I deliver the full value chain and calculate the ROI. It’s a better way to monetize the product, plus I can focus on my own solution.
As most of the customers have a huge amount of data. By bringing AI applied to all your data points, that surfaces the insights quickly into an actionable manner.
This vision embodies critical capabilities because they help telling people what they need / what they want, and as they don’t really know what to look and how to find it, this supervised learning approach enlightens them to see “what is here, what needs their attention”. It’s kind of a way to guide them, showing what’s standing out and where to start.
In addition to coloring things with sentiments, that’s important that unsupervised and supervised learning need to work together. You must marry them, one to discover and one to detect your strengths. It’s more like a ladder when you’re an AI because AI is just a tech, so you need to drive up revenue with actionable insights.
How does the ANALYTICS FEATURE impact your business strategy?
If you mean “How to coordinate Product, Sales & Customer Success team”, and “how does it help us to address C-level stakeholders?” Here are my answers.
We used to sell just to the engineer developers, so as they started moving to analytics, we decided that the customers are the C-level executive because now we cover all the data of the company, and we give insights to all the departments.
About Toucan TOCO
Our mission: tell Business Performance Stories through interactive Data and Data Storytelling.
Our users: Marketing, Production, Finance, Human Resources, SalesForces and Top management of Big Companies.
From 4 partners to 90 employees in 5 years, we were self-financed until 2019, thanks to the support of more than 100 clients, for more than 300 projects, including Renault, Crédit Agricole, Elior, Icade, Nexity, EDF, GRDF, BNP Paribas, Heineken, Marques Avenue, Euler Hermes, BIC, SNCF… We have completed our first funding from Balderton Capital and the former founder of Business Object to accelerate our development in the United States.
Small apps are mobile, easy to use, made for action and easy to set up in any information system.