One of the common best practices for large scale chat teams is maintaining a library of predefined content: hand-curated responses that agents use throughout a conversation to maintain consistency and increase response speed.
Agents rely heavily on these responses and managers spend a ton of time investing in keeping them up-to-date, but is it worth it? While there are benefits, predefined content is not without drawbacks including slower ramp time for new agents, reinforcing the performance gap between bottom and top agents, and costly time spent by agents and managers managing the system.
Companies with industry leading chat practices have begun to realize this and are ditching their clunky predefined content in favor of more intelligent suggestion systems. These intelligent systems augment agents and help maximize performance instead of limit it. In the rest of this post, we'll explore why predefined content limits performance and what is the new status quo that is emerging for intelligent chat systems.
In a lot of ways, using predefined content is like using a paper map for navigation: it gets the job done but it’s cumbersome, not easy to use, and static - it doesn't change. If you were going on a road trip tomorrow, it would be crazy to rely only on a paper map! You wouldn't know when the optimal route changes, or when to avoid a certain section, or how to take a shortcut that speeds you up. It limits your performance. Is this the same type of technology you want your team to utilize when there is customer satisfaction and revenue at stake?
Specifically there are four main problems with predefined content:
1. Predefined content isn't dynamic. By nature, predefined content doesn’t change. These databases constantly out-date themselves, and require excessive amounts of human effort to update accurately and frequently. On its own, predefined content fails to keep up-to-date with current best practices, and is unable to capture the real behaviors of actual top-performing sales agents.
2. Predefined content lacks context. Predefined content is built to be applicable in various situations; however, purposefully generic content is a poor resource for agents who work in highly situational contexts. Each conversation entails a customer with a unique personality and set of requirements, which predefined content fails to fully address.
3. Predefined content is hard to use. For new agents, searching for the right response is a considerable task, but how would they know which recommendation to use? Even if their predefined content covered every situation, it would become too much for the inexperienced agent to effectively navigate.
4. Predefined content reinforces the skill gap. It’s critical to consider that chat teams are not homogenous - your top agents hold very different conversations from bottom agents. Predefined content favors top performing agents who already know what to look for, whereas less experienced agents lack the expertise to make the most appropriate decisions. Consequently, newer agents progress at a much slower rate, widening the skill gap.
These collective issues harm the agent experience and while there are positives as opposed to not having predefined content at all, across the industry there is a realization that using only a predefined content system is limiting the agent experience and business impact.
If predefined content is like a paper map, Cresta is like turn-by-turn directions for agents. It's a radical departure from status quo, providing agents with real-time suggestions that are learned from top agents and successful conversation outcomes leading to a dynamic, contextual, and easy to use experience that makes each agent on the team an expert.
Along each point in the conversation, agents receive guidance on what to do and what to say based on similar historical situations. There is no searching, no content management, no single set of content trying to be forced into every situation. It's a novel and easy to use experience that is changing the game for leading chat teams and leading to more revenue, greater efficiency, and faster ramp up speed for agents.
In a future post, we will explore what makes Cresta so effective and how to choose the best system for your team in a changing landscape filled with chatbots, rule-based systems, and buzzwords galore. In the meantime, you can read about how Cresta partnered with Intuit to drive millions of dollars in additional revenue for their sales chat team.
Thanks to Rawan AbuShaban for help with drafts.