Agile experience management platform Momentive, formerly SurveyMonkey, revealed new capabilities of its customer experience (CX) platform GetFeedback to help users create and close feedback loops faster.
The new features are designed to help CX professionals drive better experiences across the entire customer lifecycle faster, iterate with ease and deploy without requiring expensive consultants. Specific releases include:
- Embedded Listener, an API that extends the GetFeedback platform into any offline, proprietary or secure system;
- Program Accelerator, now available in beta, designed to enable users to quickly build and launch turnkey programs based on CX best practices;
- Updates to AI- and machine learning-powered Insights, including more in-depth open text analysis; and
- The availability to show Sentiment Analysis in 10 different languages and translate the text to English.
To learn more about the trends fueling the industry-wide shift of CX prioritization, Demand Gen Report sat down with Craig Shull, SVP and General Manager of GetFeedback, to dive deeper into the updates and the CX trend as a whole.
Demand Gen Report: What inspired your team to innovate GetFeedback with a stronger focus on CX?
DGR: What would you say are Get Feedback’s focus areas for CX throughout 2022?
Shull: One of the biggest areas is AI — and guess what? That’s a buzzword for every company on the planet right now. What’s unique about GetFeedback is that it’s part of Momentive, and Momentive collects six billion responses a year and has a strong machine learning and AI team. I’m taking the power of Momentive’s AI and embedding it into GetFeedback to provide those sort of insights and tell our customers what to see in the data.
We’re also continuing to evolve our program accelerator by releasing a net promoter score (NPS) program. There are three or four other programs our customers ask us for help with, and we’re helping them by building the NPS program out. Finally, we’re expanding our integrations into other CRM data sources. We want to use the customer data to provide a better CX.
DGR: What do you think are some external factors that contributed to this demand for more comprehensive customer experiences?
Shull: I always bring up HBO — the company realized it can simultaneously release a movie in theaters and on its streaming platform, HBO Max, without a negative revenue impact. The execs realized that $1 in subscription revenue is greater than $1 in theater revenue, so HBO wants to get more people signed up for HBO Max. What’s interesting about subscription services is that if you want your customers to stay around for a long time, you have to give them a good experience.
Of course, the HBO example isn’t applicable to all industries, but what you’re seeing is that a lot of people are going digital really quickly. And in the digital environment, there are two things: Buyers typically don’t want person-to-person interactions, so as an organization, you have to be listening and acting all the time. And when all interactions and transactions are digital, it’s easier to collect feedback. There no paper surveys that you drop in a box; it’s in the moment as a buyer engages with a website or app.
DGR: What are your CX predictions for the upcoming year?
Shull: Digital acceleration is not stopping — you know, I haven’t bought anything that’s not on Amazon in almost a year, and I think that’s the same for almost everyone else right now. The move to digital is definitely happening and customers want a consistent experience across all different channels and touchpoints. The interesting thing is that there really haven’t been systems that allow feedback across all touchpoints, and that’s what the CX industry is helping.
CX is typically a bit siloed: Your support team measures CSAT on cases, but it’s much different than the website that marketing owns, which is different than the products that sales owns. So, companies are bringing all of that data into one place so when Person A interacts with their support team after the sales team, the support team can acknowledge them by name, discuss the specifics of what they looked at and identify the experience they had. As the amount of data scales across all these different channels, AI and machine learning are even more important to pull out all the nuggets of wisdom from that data.