TSIA asks our membership about different metrics and practices through various inquiries, surveys, and benchmarks. One statistic that has surprised us is the number of Customer Success organizations that use a dedicated customer success platform. According to our data, we found that 67% of Customer Success organizations do not use a dedicated customer success platform.
While the data is consistent, we continue to be amazed. Between the two of us, we have direct experience with customer success platforms, and remain connected with new technologies that continue to hit the marketplace. We have also observed how other Customer Success organizations benefit from this kind of technology with efficient results. But none of the oft-quoted benefits have carried over to moving the needle on whether Customer Success organizations will purchase dedicated tools or applications for their teams.
What Technology Are Customer Success Organizations Using?
It's time to look at and understand what this 67% are doing. When this topic comes up in discussion with TSIA members, we see three important elements of combined technology that takes away the advantage of a dedicated platform. The challenge is that with customer success processes still nascent in the industry, using a generic tool instead of a “best of breed” platform means finding your way in the dark.
#1. Customer Relationship Management (CRM)
The promise of customer relationship management (CRM), i.e., 360-degree view of the customer, has been largely elusive for most companies, with islands of customer data never integrated to the CRM master. One survey of TSIA members said contract and entitlement data was stored in an average of 13 separate systems. Relying on CRM for a broad understanding of account health and renewal likelihood will only paint a small part of the picture, and TSIA recommends investing in “best of breed” customer success technology to more accurately assess account health, automate recurring revenue, and fully explore the customer experience.
#2. Business Intelligence Capability
While there are powerful business intelligence (BI) platforms available, for most companies it will take a team of data scientists to design analytics and dashboards for customer success, and you are figuring it out as you go. The most popular customer success platforms come with predefined reports and dashboards based on what's working for hundreds of companies, so you can hit the ground running without a single data scientist.
Though CRM does allow basic process modeling for existing workflow objects (case, task), building entire customer success processes from scratch will be a major development project, and relies on your own ideas, not industry best practices. The work management capabilities of customer success platforms include libraries of the best and most efficient processes from other companies, allowing you to avoid reinventing the wheel.
The Future of Customer Success Technology
The discussion of “best of breed” is balanced with budgets, IT resources, and the ability for a company to create their own customer success platforms via customizations to stand alone solutions in the aforementioned technologies. However, every time we speak to a customer success platform vendor we get more excited about the use cases and possibilities for Customer Success organizations. So, the balance of “best of breed” against customized solutions will continue on.
Machine Learning and Artificial Intelligence
But what if these Customer Success organizations are patient, savvy, waiting for a broader leap? Machine learning and artificial intelligence (AI) have been hot discussion items within our membership, and TSIA hosted a well-attended session at our last conference on these topics. We have seen two early examples from customer success platforms that are beginning to see these capabilities creep into customer success. Gainsight and Totango have recently introduced AI-powered bots that live in collaboration-specific tools like Slack. These bots allow users to ask questions and receive alerts on customer-specific information like recent NPS scores. But most importantly, they center around the customers information.
It’s still fair to ask if this is enough to see some level of movement on the data. It may take a further leap utilizing a combination of adjacent technologies that finally turn the corner. There was an interesting Reuters article in the last few months, that has floated some interesting use cases using the converged Microsoft capabilities. Here is a quote from the article:
The new features will comb through a salesperson's email, calendar, and LinkedIn relationships to help gauge how warm their relationship is with a potential customer. The system will recommend ways to save an at-risk deal, like calling in a co-worker who is connected to the potential customer on LinkedIn.
While the specific reference was to a Sales use case there are countless customer success use cases Microsoft can execute when combining CRM (Dynamics), AI (Microsoft Intelligent Cloud), Office/Outlook 365, Social Media (LinkedIn), and the other assets available. We're hearing rumors of development around these capabilities going on in Redmond, and hope to see them scheduled for a product release soon.
Where Does Customer Success Technology Need to Go?
While it's great to speak on core customer success metrics of renewal rates, expansion rates, and reducing churn there's a problem with that. These are all supplier metrics, so the first move for customer success technology needs to begin to focus and think vertically. In the world of healthcare, there is a massive concern with cost and efficiency. Shouldn’t technology suppliers that service healthcare companies help meet the needs of those healthcare companies and solve their challenges? This would include metrics like reducing nurse turnover or improving patient care. Customer success technology can help here by understanding core vertical metrics and aligning the OEM back to those basic challenges that deliver against the promise of your technology.
Only 25% of Customer Success organizations are using data analytics to predict churn and 13% are using it to predict expansion opportunities.
Second, the technology needs to help Customer Success organizations become more predictive. We must look at our core capabilities like evaluating and monitoring Health Scores and see how we can evolve those and limit surprises. We're kidding ourselves if we as a broad customer success community think we have figured this out. One of the great myths of customer success is that born-in-the-Cloud companies have all this great data and use it to execute against supplier outcomes, like increased renewal rates and more expansion opportunities. The data doesn’t support those talking points. Only 25% of Customer Success organizations are using data analytics to predict churn and 13% are using it to predict expansion opportunities.
Finally, the technology needs to embrace the wave of artificial intelligence. We mentioned earlier the gains of some of the customer success platform vendors. But the democratization of AI needs to move beyond buzzwords. Obviously, this is easier said than done, but maybe this will be a catalyst to push more companies to make more investments in customer success technologies.
About Author Phil Nanus
Phil Nanus, is the former vice president of customer success research for TSIA. In this role, he worked closely with member companies to deliver research and advisory programs focused on helping them optimize their customer success organizations and effectively deliver customer outcomes. Throughout his career, Phil has held various positions related to enterprise software and IT services, including global leadership roles in customer success, support, professional services, managed services, and cloud services. Prior to TSIA, he was the vice president of customer success at Infor, where he led a team of Customer Success Managers (CSMs) focused on driving customer adoption of their technology.
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About Author John Ragsdale
John Ragsdale is a distinguished researcher and the vice president of technology ecosystems for TSIA. His area of expertise is in creating strategies for improving the service operations and overall customer experience by leveraging innovative technology. John works closely with TSIA’s partner ecosystem, identifying leading and emerging technology vendors whose products help solve the key business challenges faced by TSIA members. He is also author of the book, Lessons Unlearned, which chronicles his 25-year career inside the customer service industry.
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