Intelligent bot technology is disrupting almost every industry, with everyone from Verizon and Capital One to NASA jumping onboard. But while artificial intelligent is certainly not a new concept, developing and implementing virtual support agents in a practical and profitable way is still in its relative infancy. Unlike other, more established technologies, there aren’t necessarily any real standards for using bots. Thankfully, there are things we can learn from those already paving the way. Here are five real-world tips to help your company bring a VSA initiative to fruition.
Identify audience and need.
For VSAs to produce ROI, they must solve a specific problem (or set of problems) and/or deliver real, measurable improvement (such as with staff efficiency or productivity). As such, the initial phase of your virtual support agent strategy should involve identifying who you are trying to help and exactly why. The narrower you can get with this step, the better the outcome. Keep in mind you may have multiple iterations of the same engine, based on the user you are targeting.
Select a platform.
Once you have a clearer picture of your target user and target problem, the next step should involve choosing a platform through which the bots will be built and managed. This is the phase of the project that can overwhelm some decision makers. The good news is, there are platforms (like Ayehu) that are so easy to use and quick to implement that you can be up and running in mere minutes – no coding or scripting required. Even if you have a highly talented IT team, this would be the best case scenario.
Define your measure(s) of success.
One of the biggest challenges of virtual support agent (and artificial intelligence in general) is proving financial value. The easiest and most straightforward way to approach this is to determine as early as possible which metrics matter the most. What type of ROI do those in the C-suite and/or other stakeholders expect out of this initiative? Bear in mind, also, that some measures of success aren’t as easy to quantify, but are just as – if not more – important, such as end-user engagement levels.
Start fast – don’t wait for perfection.
Many people make the mistake of trying to make things perfect before rolling out their project. Instead, the focus should be on building fast and executing fast, even if that involves some degree of failure in the process. Take, for instance, NASA, which approaches each VSA initiative as a small startup with the goal of launching as quickly as possible. If you cannot iterate that fast, optimize the process as much as possible. For example, while Verizon was developing their Mix and Match bot, the consumer plan was being developed simultaneously. This made the actual rollout more seamless and successful.
Adjust and learn continuously.
A virtual support agent strategy isn’t something you set and forget. There is also the need for continuous adaptations and ongoing training to consider. Artificial intelligence is a fluid technology, which means your bots should continue to learn and improve over time. There will almost always be something to add, whether it’s a new term or a tweak in “personality” to better serve end-users. The main thing to remember is that VSA development is an ongoing process and must be treated as such if it is to be successful.
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