Last year, Genesys launched a tokenization model to reimagine contact center pricing.
In doing so, the CCaaS Magic Quadrant leader confronted a critical issue that many industry competitors are struggling to come to terms with: the demise of license-based pricing models.
These models tied a contact center’s tech costs to their agent seat count.
However, as AI promises to reduce contact center headcounts, CCaaS vendors have created a rod for their own backs.
As such, many are starting to rethink their pricing models to safeguard their businesses and ensure fairness for their customers.
That’s leading them to several possible alternatives. Yet, each has its drawbacks.
The Contact Center AI Pricing Dilemma
Consumption-based AI models are a highly touted alternative to seat-based pricing.
After all, they enable pay-per-use, offer freedom to experiment, and have many benefits for a contact center with fluctuating contact volumes.
However, the consumption route requires a flexible financial planning approach that many businesses aren’t set up for.
“People don’t like volatility in their bills,” Liz Miller, VP & Principal Analyst at Constellation Research, recently told CX Today.
As AI-driven interactions increase, and seasonal interactions start to scale up, companies are seeing unpredictable price spikes – something the CFO particularly dislikes.
A much more predictable alternative is subscription-based pricing. This model simplifies financial planning and serves contact centers with steady, predictable traffic.
Nevertheless, it’s got downsides. For instance, its fixed nature means that some businesses may pay for much more than they use.
Given these flaws, more innovative AI models have come to the fore.
For starters, there’s outcome-based pricing, which Zendesk has recently experimented with. It’s an extremely attractive option for many customers, as they only pay after achieving success. Yet, defining what “success” looks like – on a customer-by-customer basis – requires a lot of negotiation.
A similar model has the vendor and customer analyze the revenue driven by contact center AI to split the earnings. While that may inspire close end-user relationships, it’s again tricky to define and adds complexity.
Finally, consider a freemium model that gives away “starter” AI use cases for free. As customers begin to use more, they may switch to paid plans. However, these plans may not align with the customer’s needs. Moreover, costs can spiral with such a “layer cake” model.
As all these examples showcase, this pricing problem has no silver bullet. But, with its AI Experience tokens, Genesys may have found the closest thing to it.
The Genesys Tokenization Model
With Genesys Cloud AI Experience tokens, contact centers can choose the AI capabilities they’d like to deploy and pay for only what they use.
So, service teams can take a modular approach and scale up if they’d like to implement a virtual agent, predictive engagement tools, AI summaries, etc.
That modularity is essential, enabling a more cautious strategy for AI implementation that avoids the volatility of a fully consumption-led model.
Moreover, it allows contact centers to activate new AI features as they evolve, so they may experiment without unnecessary expense.
Arpita Maity, Director of Product Marketing AI at Genesys, shared more on the model’s advantages in a Genesys blog post.
“Tokenization in AI is a way to track AI engagement in real time by allocating fixed units of measurement to usage costs,” she said. “This can help businesses of all sizes allocate resources dynamically and efficiently.
By paying only for the AI functionalities you actually use, tokenization offers a scalable, cost-efficient way to integrate AI into your operations.
That scalability is especially critical in helping contact centers forecast AI maintenance costs so they can consider the total cost of ownership (TCO) and better gauge ROI.
As such, Genesys has pieced together a strategy that aligns well with the walk, crawl, run contact center AI strategy.
Of course, some may wish to jump in at the deep end, but this approach matches vendor’s overall framing of itself as a strong, reliable CCaaS partner.
