The days of gathering customer experience (CX) data after the fact are over. In the early years of gathering information about customer impressions and experiences, the CX thought leaders at OCX Cognition have seen traditional CX approaches flounder and flail their way into irrelevance.
Along the way, they came up with a new way to analyze CX: predictive analytics. Getting out in front of CX concerns before they happen — not reacting to them after poor customer satisfaction survey results — is the only way to keep up with the break-neck pace of commerce.
Current CX systems fail companies 95% of the time. Relying on a system that fails more than it delivers will get companies nowhere. With OCX Cognition’s game-changing approach, they don’t have to rely on the old ways anymore.
Out with the Old Ways of Doing CX …
Look as long as you want — you are not going to find a company that doesn’t claim to put customer satisfaction and experience first. That’s a good thing, of course. But, the ways in which companies prioritize CX are, by and large, tired and ineffective. Here are the old ways companies have tried to do CX:
Relying On Call Centers
This is the hands-off approach to CX, and it signals to customers that everyone—from ownership to management to staffers—cares minimally about customer satisfaction. Call centers often lack the context to effectively address customer complaints. Companies that employ them are happy to rely on their customers’ responses to these strained-at-best interactions as the entire data set they use to analyze customer experiences and satisfaction.
Using Customer Success Managers and Account Managers
Account managers (AMs) and customer success managers (CSMs) give customers a somewhat more direct line of communication with companies, but this CX model comes with an inherent problem: CSMs and AMs are human beings, and they introduce human biases and human error.
As account managers, CSMs and AMs are low enough in the corporate hierarchy to command exactly zero authority in a customer-company interaction, but authority is exactly what’s needed to record CX data, synthesize solutions and implement change. The translation of CX data from the CSM level to the CEO level leaves companies with insights that are as clear as TV static.
Sending Out Surveys
Customer satisfaction surveys solve the human problem introduced by CSMs and AMs. They are more or less objective and provide data that’s relatively easy to understand and interpret. Great. But if no one takes the survey, there’s no point. And that is so often the case with CX surveys. Participation is incredibly low — around 3% for some B2C companies — and data is skewed because those who are motivated enough to respond are often motivated by anger.
All three of these existing methods of CX analysis are flawed in their own ways, but they’re unified by one flaw they all share: they all provide information after the fact, when the damage is already done.
… And in with the New
In coming to understand the flaws inherent in existing CX analysis models, OCX Cognition saw that a new approach isn’t just beneficial — it’s absolutely necessary. So, they developed their predictive CX analysis software. Here’s how it’s different from the traditional way of recording and interpreting CX information:
- It follows the customer throughout the entire customer journey.
- It uses AI to predict how operations will impact customers.
- It gathers real-time information about each customer every single day.
OCX Cognition brings operational and attitudinal data together to provide a product that sets itself apart from traditional CX analysis methodologies. Companies that adopt this new approach will, without a doubt, gain an advantage over competitors who are stuck in the old ways.
The industry-standard net promoter score (NPS) provides a clear example of how this new approach works. NPS tells companies whether customers are promoters of their products and services or detractors. It’s not a binary choice between promoter and detractor, but the nuance on the spectrum used to understand NPS data is still typically gathered through surveys.
Here’s what you don’t get from NPS surveys: the thinking behind each answer choice. And companies need that information to be able to respond to CX concerns effectively.
OCX’s new CX model adds operational data into the mix. Combining these data sets and analyzing them with AI allows companies to link the reason why a customer is dissatisfied to a concrete process or interaction along the customer journey.
Automated CX data set aggregation and analysis enables analysts to drill down to individual customers, then build customized plans that promote retention on a granular level. Doing this in real time allows companies to act before they lose a customer or client.
Predicting, Not Reacting
With AI and machine learning as driving forces, OCX Cognition’s software is empowered to provide more insightful insights over time. It grows and learns with your company. This approach puts an end to mysterious customer retention problems — all you have to do is look at and respond to the account-specific predictive scores the program generates each day.
Predict risk and reduce it. Don’t wait for it to happen and then react to it. This is what OCX is allowing future-focused companies to do. Your customers are speaking right now, and this new CX technology allows you to listen in real time and react with time to spare.