Every day, a new technology provider seems to crop up, claiming to revolutionize customer service with their latest AI solution.
Amid this noise, separating the wheat from the chaff is more difficult than ever.
Recognizing this, CX Today contacted Ian Jacobs, VP & Lead Analyst at Opus Research, to isolate the most critical considerations to mull over when selecting a contact center virtual agent.
Below are five of those considerations, alongside a set of baseline capabilities every prospective conversational AI provider should offer.
1. The Best-Placed Pricing Model
There are many pricing models in conversational AI, and vendors are continuing to experiment. Some add options to existing models, while others move toward entirely new approaches.
Here are four of the most common models available today:
- Price per agent – This mimics the traditional contact center FTE replacement model.
- Price per action – This is a consumption model, based on what the agent does.
- Price per outcome – This performance-based model aligns with the agent’s success rate.
- Price per workflow - This supports full work automation, as the agent completes specific sets of actions.
Each model has pros and cons, and each suits a different type of brand. To decipher the best-placed pricing model, Jacobs suggests:
“Brands need to ask: Are we just starting out, or are we scaling fast? What kind of ROI alignment do we need? Do we need predictability or flexibility?”
That last question is perhaps most important. After all, if a contact center has lots of variable traffic and can't predict usage, then a consumption model makes sense.
Meanwhile, a performance-based model may be a better option if a brand is scaling fast and is happy with its ability to track agent actions, outcomes, and ROI.
2. Usability for Real Teams
It's becoming easier for non-technical teams to write prompts and build a bot. However, that doesn't mean they should take the reins of virtual agent projects.
Instead, contact centers have a big decision to make: how much accessibility should we give to non-technical users? And beyond that, what does day-to-day manageability look like?
They may no longer need traditional speech scientists, but they will need people with real expertise, such as conversational designers.
A contact center’s capacity to establish that IT expertise should be a key factor in selecting the ideal solution, as some are more accessible to non-technical users than others.
3. Integrations Beyond Just APIs
Having APIs for adjacent systems is table stakes. But, many contact centers are considering how AI fits not just the contact center silo but the broader enterprise ecosystem.
Why? Because resolution flows often cross front, middle, and back office systems. To automate these interactions, contact centers require a deeper level of integration.
Among is burgeoning co-innovation relationships, Zoom CX – a provider of the recently launched agentic Zoom Virtual Agent (ZVA) - has teamed up with ServiceNow to establish such an integration. Thanks to that, ZVA can pull data from and trigger actions within middle and back office systems.
Take insurance, for example. Zoom can take a process that starts at the contact center, move to an adjuster in the back office, and then loop back to the front office to communicate with the customer. That end-to-end integration matters.
As other vendors follow suit, some are now considering pricing based on that entire workflow, regardless of how many steps it takes or where those steps occur. That’s a fascinating idea.
4. Real-Time Performance Tracking
In conversational AI, it's essential to have a live view of what's happening, and ideally, a system that can recommend corrective actions.
That’s where the future lies, in self-learning systems that can say: "Hey, if you gave me access to this data source, I could resolve this issue myself."
Such prescriptive reporting should be a roadmap capability, but also real-time analytics that don’t just present a dashboard, but highlight specifically where the problems are.
For instance, let's say the business has set some parameters for its virtual agent, yet conversations about a common pain point consistently fall outside those limits. That should be flagged so the contact center can investigate and perhaps implement a rules-based flow instead.
Summarizing this point, Jacobs said: