Editorial
Whether you’re asking Google Home how to make a soufflé or using chatbots to offer better customer engagement, artificial intelligence (AI) is as diverse in its implementations as the people who use it.
The biggest barrier to launching an AI-focused strategy is often thought to be the high cost, but that doesn’t have to be the case.
As with any digital strategy, understanding the need and clearly defining it are essential for having an overview of the benefits AI can bring to your company. Then, by mapping the scope to a realistic timeline, it is possible to see that the introduction of new digital channels can be iteratively delivered in working-version stages, and then tested, improved and expanded upon over time.
As an example, let’s consider a chatbot deployment.
To justify building out a chatbot, you must first understand the role it plays and the “why.” Chatbots offer an excellent way for your customers to interact with you, and when you combine that capability with a good content management system (CMS), you are able to manage micro engagements through the creation rules or algorithms. As a result, you can have an always-on channel that is available wherever your customers are and forms a powerful communication interface between you and them.
Related Article: Chatbots Belong in the Workplace (Provided They're Well-Designed)
What Comes First, the Chatbot or the Egg?
Before getting overexcited about having a hip, new chatbot, you need to consider the cost and your capacity to support such a system over the long term. Swift adopters beware: If you are not able to maintain your new system’s relevance, you run the risk of creating a digital albatross that produces a negative experience for your customers — who are the people you initially planned to help and the ones who generate all that lovely money. So being mindful of the operational expenses and having a clear idea of how you will manage and maintain your chatbot are key to kicking off the project successfully.
The next stage is to build a prototype that is small and manageable and can be tested on a small segment of your target audience. This approach enables you to keep an eye on the chatbot’s relevance and usability and, most importantly, identify the ways in which you can improve it based on actionable feedback from the customers who use it. Adding this flexibility to the project means you can shape it more precisely based on the needs you identify along the way. And because you have segmented your audience, you know that the people you are gathering input from are actually people who already buy and use your products and services.
Related Article: What Makes a Chatbot Tick?
How Long Is a Piece of Digital String?
It doesn’t have to take very long to launch the prototype. It’s possible to go from the initial planning phase to a working prototype in less than a month if you avoid complexity at the start. As is the case with any digital strategy, ensuring that things go smoothly involves recognizing your customer touchpoints and testing in a way that ensures that the data you collect can influence the chatbot’s implementation and development.
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The Meaning of Chatbot Success
Every marketing initiative should be backed up by key performance indicators (KPI) that are realistic, right? But what does success mean for your chatbot project? And because you’re taking an iterative approach, can you redefine success based on data coming from test of the prototype? Launching a beta version answers questions such as those in many ways, but it also raises others. Initially, you can say that you want to add an automated 24/7 way to engage with customers. But what benefit does that bring? Do you want to be able to understand where customers are in the buyer’s journey and encourage them to sign up for news and offers? Or do you have an opportunity to use their demographic information or previous sales and site histories to “talk” them into making a purchase — or even get them interested in a cross-sell or upsell option?
Related Article: Why I Hate Customer Service Chatbots
Critics Gonna Criticize
It is strange to see a Luddite mentality in the 21st century, but you will encounter people in your organization who are cynical about chatbots, and you will need to get them on your side (it is, after all, a company decision).
If you are able to launch a working prototype quickly, the skeptics may realize that a chatbot isn’t just a gimmick once they get to see it in action. The verifiable data gathered from the “exciting” technology will speak volumes (which is ironic, for a typically silent chatbot) and will help turn detractors into advocates. Therefore, having metrics in place that measure the project’s success gives you the structure and approach necessary to have a sensibly integrated omnichannel strategy that in itself creates a unique and enhanced customer experience that can offer impressive adaptability and accuracy in the way it responds.
Once you have the right technology in place, complexity and cost are no longer seen as insurmountable roadblocks to using AI technology to improve customer relationships. The fact that you can scale AI at a manageable rate means you can use this cutting-edge technology to gain an advantage over competitors that may be too cautious or may not fully understand the technology — and are therefore missing out on the added revenue and the improved customer loyalty that improved engagement brings.
The main points to remember are that you need a well-defined AI strategy based on a clear understanding of what success means, and that you need the KPIs to measure success. With those elements in place, the path to a well-delivered AI experience is suddenly much easier and more cost-effective.
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