We hear there have been developments at Rollio, how has the development process been in the current market?
We certainly haven’t slowed down! Our teams have been working hard to ensure that everything we build comes from data and feedback we gather from our customers. One of the biggest concerns is Voice-to-CRM, which is why we’ve worked so hard to make our speech to text quality accuracy what is. Our own phonetic algorithm allows for all users to speak in their own company language (customer names, product names, etc.), where as with other speech to text tools you are used to hearing “sorry I didn’t understand that’ Rollio is trained for you, not a generic, one size fits all, dictionary.
The setup and change management of Rollio has been reduced to zero code and almost a drag and drop facility. With this high-quality AI model there is no heavy lifting, translating to fast deployment and quick to trial the full solution tailored to your company.
Our desktop solution has been a huge productivity boost for inside sales teams trying to make up for the current situation by increasing volume. For service teams we’ve greatly reduced training costs at contact centers by $80k+ on average and significantly decreased handle data entry time. This allows reps to take up to 40% more interactions per day. This is essential as customer NPS is more crucial than ever right now.
AI can sometimes be seen quite broadly, what are the key points you are focused on?
We’re an NLP company, natural language processing. This means we’re really good at, and passionate about, making text and voice (the unstructured data that gets lost every day in emails, text, conversations) actionable and drive a hard dollar return whether it be for sales or service. It’s easy to capture close dates, product names, and stages of deals and cases, but far too many companies are reporting on activity without any context. If your users say it, and it’s meaningful valuable customer intelligence, Rollio grabs it: more data in a fraction of the time, but also valuable data that actually stays up to date.
AI has a learning aspect where it builds on data, do you recommend all companies have an AI Strategy?
I certainly can’t speak for all companies, but I can say we work with small 5-10 person companies that have seen their sales people fit in 15-20 more meetings per week due to voice-to-crm and we’ve worked with 1000+ companies that see huge increases in pipeline activity, forecasting accuracy, and customer service centre savings. AI can appear to be this big scary thing, but if you work with the right partner and discuss a plan tailored for you then there’s definitely hard ROI and value to be had.
Is this the end of the ‘front end’ and ‘back end’ process?
I wouldn’t say end of, but we’re definitely creating an environment that better segments them, in an effort to fix a front-end that’s been ignored for too long and a backend that requires to be fed data from a friction filled front-end. CRMs are built for the organizations but sometimes in that process we forget what we’re asking of the user. So, we decided to think about the user by making data entry simple, and in doing so the net ROI is huge for the backend (‘organization’) trying to run their business’s marketing strategy, demand planning, hiring, and forecasting off that information.
How is AI useful to companies, how do you handle misconceptions?
Two things: It doesn’t have to be a big, scary implementation, you can onboard AI in bite sized chunks, plus the companies doing AI correctly will know how to implement it smoothly. Additionally, there’s real AI and ‘not so real AI’, which is definitely something to look out for because not so real AI is usually basic process automation that you can build yourself for a fraction of the price, but at the end of the day if your business is getting a return on a solution, then does it really matter.
So, we have Rollio Service Assist and Rollio Sales Assist, what next?
We have a lot on the roadmap in terms of capturing data that too frequently gets lost or forgotten from other sources that sales and service reps work with. Our goal remains the same: let users do less data entry work, making them each more valuable in a unit economic sense to the business, ensure the business is capturing increased and improved data which is why they invested in a CRM in the first place, and of course just make users’ lives easier. As well as some neat predictive insight capabilities too!