By Swapnil Jain, CEO, and cofounder, Observe.AI
Anyone who has worked in retail will tell you that communicating and forming a connection with a customer probably works best face-to-face. In the age of COVID-19, these face to face interactions is now scarce or non-existent, leaving a swath of retail interactions to fall on the shoulders of contact center agents.
This shift in the way consumers and brands are communicating is all the more relevant as the major promotional holiday season starts up. Many large brands like Walmart and Best Buy are extending these seasonal promotions and shifting their promotional offers online to meet the rising demand for e-commerce. They are doing so for good reason. Recent data from Adobe Analytics demonstrated that in the first eight months of 2020, there were over $497 billion in online sales alone. As of August, there have been 130 individual days where sales exceeded $2 billion (compared to 2019 where only two days individual days matched $2 billion). Likewise, the practice of buying online and picking up in-store (BOPIS) has seen a 259% increase compared to 2019. Simply put, with life becoming increasingly remote, online sales are booming in an unprecedented way. To succeed, companies must create proper remote services to meet this considerable remote demand.
Not surprisingly, with this unprecedented boom in e-commerce, contact centers are more overwhelmed than ever. This is understandable considering that they are essentially seeing Black Friday and Cyber Monday levels of phone traffic and customer inquiries every single day. Every company is keenly aware of this and working hard to compete for this booming online retail demand, making the quality of call center services more important than ever.
Naturally, one would hope that with this rapidly rising demand for contact center customer service interactions, contact center agents would see an appropriate increase in training and support. And with most agents now working remotely for the first time, that training and support are even more critical. Sadly, this hope for increased contact center training has not materialized.
This Call Is Actually Not Monitored The Way You Think It Is
Everyone has heard the “this call may be monitored for quality purposes” message. However, this quality assurance is rarely ever met. In fact, only 1-2% of contact center calls are monitored, and it’s done manually. On those calls that are reviewed, in many cases, feedback and coaching are delivered two weeks after an issue occurs, and as a result, does nothing to help frustrated customers. Equally important, it doesn’t help agents learn and grow.
Creating a solution to this unanswered problem is not quite as simple as hiring more agents. In fact, given the average budget of a company in 2020, it is simply not realistic or advisable. The most realistic solution is better training. It is now more critical than ever that companies find a way to effectively coach agents around the soft skills that directly impact the most mission-critical call center KPIs to improve overall customer experience and ultimately do better business this holiday season and beyond.
Better Coaching = A Better Experience For Everyone
This will all be possible with the help of contact center software built around providing training and feedback to these important call center agents. Companies need to provide both an avenue for call center agents to receive data-driven feedback and the coaching that will prepare remote staff for this new competitive online environment.
The primary goal of any modern call center is to have agents that are meeting customer demands at the highest possible level. The current volume of calls and requests that these agents are required to handle during the pandemic is making that challenging. As agents are handling increased customer interactions, some of them may not go perfectly. Agents need to be able to learn from these negative interactions so they can be remedied and prevented in the future.
Providing feedback on customer interactions is necessary for the improvement of an agent’s overall skills. Subsequently, the current lack of feedback provided to these agents is the greatest hindrance to their success. To be useful to a call center agent, the feedback provided to them must meet three critical criteria.
Firstly, this feedback has to be data-driven. Interacting with remote customers via the contact center can lend invaluable data to learn from if it is captured, quantified, and observed. Simply put, feedback married with context is more impactful.
Secondly, feedback needs to be personalized. When an agent is receiving feedback on a given call, they need the feeling that this call is relevant, even unique, to them. With that in mind, feedback in some way must provide an honest and helpful reflection of a given agent’s individual strengths or weaknesses. Maybe an agent needs to work on their initial greeting when speaking with a customer. This might be a weakness that goes unnoticed in the current model, but with AI-led coaching, it can be caught early and improved. It's also important to consider that personal positive feedback will increase the overall morale of the agents in a call center’s roster.
Thirdly, feedback has to be measurable. An agent should be able to see their progress over time. If feedback can demonstrate where an agent is growing and struggling over a period of time that agent is more likely and able to improve on their call skills.
While these criteria are all equally important to a given call center agent, none of them matter if this feedback isn’t delivered in a timely fashion. When this important feedback is delayed, an agent is left wondering what they could have done differently to improve customer interaction.
If an agent could receive near-instant feedback on how their call could have been improved, they can leverage that feedback and improve the customer experience for every interaction with a customer that follows. AI-led coaching provides this critical service. The analytical, data-driven nature of AI-coaching allows for accurate and rapid feedback to these agents to ensure the success of future interactions with remote customers by delivering feedback that is not only tailored and useful but also reaching agents when they actually need it.