Convince Your Boss To Invest In CX

The customer experience goes through several pivots in its lifetime to adhere to the ever-changing customer need. Many businesses face the reality of needing to adjust strategy more often than expected which may require new investments for these new plans. Revisiting this topic with your boss is not easy, especially when it’s hard to prove a tangible return. We connect with Colin Crowley, the VP of Customer Experience at Freshly, on how to influence your senior executives to invest in CX.

“How would you influence senior executives to invest in CX when they don’t believe that it will increase business performance? What’s the best way to get started on a CX journey in this situation?”

At the end of the day, the best means of convincing executives to invest in CX comes down to data. Data, like music, is a universal language of sorts that is able to unite people (if done properly and holistically) around key areas of concern. All too often, there is an unfortunate lack of data available when it comes to customer experiences – especially regarding the more intangible components of those, dealing with customer feelings and impressions – so you have to be mindful of collecting data proactively in these areas.

You also have to make sure you understand how that data intermingles with other key points of data, such as its impact on retention, average order value, and the other more tangible types of bottom-line metrics. One of the best ways to gather data about something unknown is to ease yourself into it, collecting data along the way and building up a “portfolio” of facts that you can ultimately hand off to an executive. If you’re looking at adopting an expensive chatbot technology, for example, you might want to consider trying out a basic, low-level bot first through a company with a low price point – something  that perhaps spits FAQ articles at customers rather than robust pre-built conversational experiences. This would reduce costs but also help to provide a baseline of expectations, because, if you can achieve X goals with a very basic bot, you know that any more expensive bot has to deliver at least X x Y% to be justifiable – with the flip side being that, if you CAN achieve X with a low-level chatbot, what else could you achieve with a more advanced version?

This type of early experimentation using up-and-coming (and cheaper) technology companies can be used across the technological spectrum with AI and RPA solutions to prove use cases and build justifications for broader investments in technological infrastructure that would be harder to justify from the get-go.