Instant gratification dominates the digital engagement space, and customer support teams are on the front line. Many consumers judge your brand based on their first engagement with care agents, who, in that vital moment, are the ambassadors of the brand. Their judgments can be harsh, especially if you don’t meet their expectations for response time. If you’re a contact center manager, taking advantage of your agents’ strengths — and understanding their shortcomings — couldn’t be more critical.
Off the bat, let’s clarify that, though they are rare, there are times when cherry-picking can be beneficial: during ramp-ups, on highly technical requests, or during rest intervals. This can help agents avoid burnout, get help where they need it, and thus improve their overall quality of service. In short, you shouldn’t expect your agents to always take the most difficult cases first, because that’s not good for them, you, or your customers.
Cherry-picking becomes dangerous when it’s used habitually — and this is exactly when you, the contact center manager, may need to step in. The practice can severely dampen an agent’s growth, and risks giving the customer a false sense of neglect from the brand itself. Remember, in this moment, that agent is the brand ambassador. And it’s up to the managers to equip them with the right tools — including a conversation management platform to represent the brand as well as they can.
Khoros Care comes equipped with a collection of different widgets to measure agent performance. They are excellent ways to detect a number of potential issues in real-time, and cherry-picking is one. Here are some of the metrics that matter when you’re trying to avoid habitual cherry-picking.
Whether agents are active within the agent dashboard can be an excellent indicator of whether they’re cherry-picking. If they’re logging a lot of out-of-focus or inactive time, they may be focusing on a different window or tab with the agent console in the background. Check how long agents go without claiming a conversation, even though the queue is active with open requests. High numbers here show that they might be passing up difficult requests to wait for easier ones.
Remember, though, not to take this statistic in a vacuum. An agent might not claim a new conversation simply because they are helping a customer with a difficult, time-consuming task. So make sure to measure not just how long they go without claiming a conversation, but also how long they go without any activity
With the right context, handle time can also be a warning sign for cherry-picking. An agent whose average handle time is far shorter than that of others may be intentionally selecting easier topics. Perhaps an even better indicator is when an agent often opens conversations and closes them without engagement.
Track how many conversations your agents handle versus how many conversations they engage. If these numbers are far apart, it can indicate that the agent is cherry-picking. Again, though, make sure to view this metric within the context of others as well, as it doesn’t always tell the whole story.
Tracking how many conversations agents assign — and even more importantly, unassign — themselves can be an excellent predictor of cherry-picking. If an agent has assigned and then unassigned themself from a high number of conversations, it’s likely that they are cherry-picking.
The analytics view in Khoros Care displays multiple widgets with graphs to provide real-time visibility into activity on your social media channels, as well as your team's performance. You can filter the data according to time range, priority, and work queue. One metric in this view that’s helpful for detecting cherry-picking is an agent’s responses per conversation. How many times an agent responds within a particular conversation can indicate the difficulty of the task: easier tasks typically require fewer responses.
First, they can implement Claim Next or Push Next — powerful options that are included as part of the team-level settings you can define for each of your response teams. This eliminates cherry-picking by simply hiding the conversation queue from agents. Instead of selecting a topic, the agent can claim (or be pushed) the next one in the queue. Since they no longer have the ability to choose topics, it is impossible for them to cherry-pick. Still, use these options with caution, as they can limit agent freedom in ways that harm the brand.
Another (less extreme) strategy is to incentivize agents to more often handle difficult or longer conversations by monitoring sentiment conversion. With a pulse on the agents giving white-glove service to complicated problems, you can easily implement incentives for proactively picking up conversations with the most frustrated or dissatisfied customers.
Every brand has its own unique cases
When it comes to how to approach cherry-picking, different brands will solve them in different ways. Still, regardless of which strategy (or strategies) you choose, it’s always a best practice to ensure incoming and current agents know the importance of engaging with customers.
Need some more info on using Care Analytics? Check out these resources.
Questions? Comments? Thoughts?
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