A graphic representation of what the infrastructure of an actual chatbot looks like. The outer nodes connect incoming communication and information, categorize them into 4 different different categorical departments, then pass them through the central platform — in this case it’s the Pypestream platform.

The 3-Step Process for Building Customer-Facing Chatbots

Bots and messaging have been pegged as the future of communication by industry thought-leaders and technology companies the world over (including us here at Pypestream). If the prediction rings true, then the user experience will shift from one that’s determined by the brand or organization, to one that’s heavily influenced by how consumers choose to connect with the business.

As messaging evolves, brands and consumers will begin to engage in conversation-based communication. This means instead of consumers navigating a company’s website and being forced to adhere to its user interface, brands will need to learn how to understand the natural language of the consumer.

The burden will shift from the consumer onto the brand, and this means businesses, brands and organizations will require a clear understanding of consumer needs and wants, and be able to answer the following types of questions:

“What questions will people have when they’re contacting our business?”

“What information will they search for?”

“Will they know what they’re looking for? Or will they need prompting?”

“What if they don’t know the wider spectrum of services we offer?”

Understandably, with the broad range of potential consumer inquiries, businesses are going to have a tough time providing an experience that feels intuitive and seamless.

Prepare your business for the ‘conversational web’

Now is an ideal time for businesses to start exploring how chatbots and messaging can improve communication to help the transition into the ‘conversational web’ era. Automation technology (read: artificial intelligence) is still maturing and we’re only just beginning to scratch the surface in terms of how it can be applied, let alone best-practices. It’s the perfect time to experiment with new technology, like chatbots, and assess how your customers react.

But where do you start?

At Pypestream, we follow a 3-step process to ensure every AI-powered bot is built to solve specific problems, and is hyper-focused on adding value to both the customer AND the business.

Take a look and let us know what you think:

  1. Auditing customer inquiries: “Where are we now?”

Before any business decision is made in any capacity, we must first determine the baseline from which we measure things moving forward, or simply, “where are we now?”

The same is true for implementing an automation strategy — before any automation takes place, there must be a clear understanding of the most common customer questions and interactions.

Start from a departmental level and determine where the biggest volume of customer interactions is taking place. Then begin analyzing individual interactions to determine any patterns or repetitive inquiries. As a general rule, the most common scenarios, like updating account details or processing bills and invoices, lend themselves best to automation.

2. Automating the low-hanging fruit: “How can we be better?

Once the initial customer communication analysis is complete, you will gain a clearer idea of which areas you can focus your automation efforts on. Choose the path of least resistance and automate the easiest inquiries to get started. This allows you to gather the relevant data that will help your automation plan grow into the future.

For example, if an airline identifies that 75% of its customer service inquiries are related to changing a reservation, and the process is highly repetitive, an automated chatbot may be used to free-up human agents for more ‘hands-on’ customer service issues, like updating baggage options or changing dietary requirements.

By starting small and analyzing where the most common and highly repetitive inquiries are stemming from, a business gets a better understanding of where there are opportunities for further automation.

3. Increasing automation: “Where do we want to be?”

With specific and commonly asked questions automated through chatbots, you can then begin analyzing how customers are responding and interacting with the chatbots to see where there are opportunities to improve or extend automation with further bots.

But before you get too carried away and start developing bots upon bots, ensure your strategy is grounded in data. Use the data from the initial interactions between chatbots and customers to gain insight into both the pitfalls and the potential opportunities the current bots reveal. Maybe there’s room to improve the current chatbot experience, maybe not.

Either way, using data to drive future chatbot implementation reduces the risk of you developing bots for the sake of it, which is likely to result in an overall frustrating customer experience.

Customer satisfaction drives the implementation of customer-facing technology, so remember the golden rule: If it doesn’t benefit your customer — don’t do it.

Bots are the new apps

The emergence and continued development of bots is likely to change how we seek information and service from businesses. Some businesses are better suited to chatbot automation than others, particularly in industries with less complex sales such as fashion retail, but overall it’s important for every business to consider how this new ‘conversational web’ will impact them, and their customers.

Contact us for more information about how our bots can bring value to your customer service strategy.

By Allan Stormon — Director of Content & Communications

Originally published at www.pypestream.com.