Interview with Alexandre Debecker, Chief Growth Officer – ubisend

Tell us about the journey that led you to start a chatbot company.

The journey of ubisend started 15-odd years ago. For over ten years, we have been developing health-critical mobile messaging campaigns in low-resource countries. Back then, sending SMS content across the world was a laborious process, messages were drafted into spreadsheets and forwarded to telecom providers. It was neither secure nor efficient, and we would not get any success and deliverability metrics back. There was a definite pain-point.

We knew there was something to be done. So, an internal team developed a platform that would allow us to plan, write, schedule, and send messages effectively. More importantly, it would also allow us to report on the success of these messages — delivery, open rate, and more.

The platform allowed us to go beyond just sending messages. It enabled us to create AI-based models that helped us time message sending better, ensuring the correct person received valuable advice at the right time, and much more.

About three years ago, the world witnessed a massive shift in the way consumers message one another. SMS had been old school for a while, and finally, mobile messaging apps (Facebook Messenger, Telegram et al.) started opening up their APIs. It was the catalyst that enabled us to be one of the first companies in the world to dive head first into humans having useful two-way, natural, conversations with machines.

We brought our messaging knowledge, our AI-power, our client base; and started building chatbots across all major platforms.

What are the challenges with traditional messaging? How do chatbots solve these?

Traditional messaging between businesses and consumers (or businesses and employees) is broken.

For the past 20 years, the relationship has been one-sided. On the one hand, businesses push messages to their customers whenever they see fit. While on the other hand, consumers cannot reach businesses when they need them. We have all experienced the dreadful ‘thank you for your message; we aim to reply in 3 to 4 business days’.

Chatbots solve this (onse-sided conversation). They turn B2C, one-sided broadcasting, into a two-way conversation. Instead of having to wait, customers can now prompt a chatbot and get answers and help immediately.

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Which industries are most impacted by your chatbot creation? What is the core functionality of the chatbot here?

At present, by far, the HR space is the one benefiting most from our chatbots. When we think about it, it is not that surprising.

HR is often an afterthought within a company. Budgets tend to go to departments that directly grow revenue, like marketing or sales. A company then grows and finds itself with a tiny, overworked HR team.

The solution chatbots provide is to remove a chunk of the burden on HR teams. As an example, a common HR deployment prevents around 40% of staff inquiries hitting HR desks. Almost overnight, the HR team gets lots of their time back. This is achieved by gathering a company’s internal documents, applying our machine learning algorithms and turning the first iteration of their chatbot into a knowledgeable member of the HR team. No expensive integrations or inside development required.

On top of this, an HR chatbot solution is not customer facing. It is a low-risk approach for a large company. It is a way to test the new technology without putting anything in front of the consumer. It is the opportunity to see what the technology can do and build a business case before further investing.

How does the process of development change across channels of communication; Facebook Messenger versus WeChat, for example?

Back when we first developed our platform, our goal was to build something that would allow our users (and us) to deploy chatbots across multiple channels, without hassle.

The ubisend platform, which sits at the core of all our chatbots and manages the sending/receiving of messages, analytics, human takeover, and more, is entirely ubiquitous.

We built it in such a way that deploying a chatbot onto any available channel is a flick of a switch; the platform does the hard work for us. It automatically downgrades/upgrades message content, delivers rich media where and how a channel accepts it and always gives the best experience possible. The use case is phenomenal; one person can be talking to a single bot via SMS, another via Facebook and someone else via live-chat. It is entirely cross and multi-channel, the experience is practically the same and all conversations, human-takeovers reporting and metrics are in one place.

What’s the top misconception people have about bots?

The industry has gone through a couple of phases. A couple of years ago, we all got excited about chatbots. Channels like Facebook Messenger opened up their APIs and helped drive rapid adoption. Apparently, chatbots were going to save the world.

Then, the hype slowed, and people become a little pessimistic. At the time, most of the chatbots in the wild were nothing more than decision trees, and the industry lost a bit of its sparkle.

Going through these two phases is common. The Gartner hype cycle shows new technologies need to go through this hype phase, then disillusion phase, to finally creep back up and plateau at a productivity level.

I believe we are now slowly going back up and heading towards the productivity plateau.

As the cycle unfolded, ubisend was smack-bang in the middle, helping the technology evolve. We were happy chatbots were suddenly popular (as we had already been building them for years) but knew what was likely to happen.

Platforms opened up and enabled anyone to build low-quality chatbots easily; it was quite clear the industry would quickly reach the low disillusion point. We knew developing effective chatbot technology is hard and required more than a simple flowchart and a few clicks of a mouse.

Today, as we head towards the productivity plateau, we need to fight the idea that chatbots are just decision trees or flow-based question/answer systems.

We also expect that once we reach productivity, the industry will drop the word ‘chatbot’ as it has a gimmicky connotation.

We do not build chatbots; we make complex machine-led conversational agents that are solving real business problems. If we do need to shorten it, something like ‘conversational software’ is much more appropriate.

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According to you, how important is personality when developing a chatbot and how does it help?

Chatbots enable us to enter a new level of creativity. Companies can go beyond iconography, colors, and images and play with language, persona and tone of voice — at scale.

Developing a chatbot’s personality is important. After all, your chatbot may become your customer’s first contact with your company. You need it to align with your company’s culture, and it brings a whole lot of fresh internal decisions to the table.

One of the first things we do with a new client is to lead a chatbot personality workshop. After all, it is something most marketers/PR/creatives have never worked on. We ask ‘so, how does your company talk?’

Should your chatbot be friendly? Formal? Does it speak like a teenager? Does it have a gender? What is its name? Does it use emojis? Does it LOL?

A well-crafted chatbot personality helps users on their journey. Should your chatbot not fit the culture of your company, people may feel awkward talking with it. Also, to keep engagement high, it is important to improve not only your chatbot’s functionalities, but also its conversational UX and language. Test everything.

How does ubisend integrate with enterprise technology?

A big part of our focus is enterprise clients. Many of our customers are Fortune500 businesses. As such, everything we do in this space is custom built.

We do not believe in templated, out-of-the-box solutions that we copy/paste from one client to the other. Each chatbot is unique, and we treat it as such. Integrating with established, internal enterprise technology is a must.

Our typical approach is to evaluate the tech stack we are going to work with during the discovery phase. We will meet with the leaders of each team to find out what we need to integrate with. If they have anything already built that will help us, we will dig into that. If not, we figure out who to talk to about making it happen.

There are no secrets here. Building custom chatbots for high-end clients means adapting to the technology they have on site. After all, no one wants a chatbot that lives in a vacuum or to have to log in to another piece of software. Integration is key.

That being said, depending on the solution, things do not have to get super-integrated. Typically, our initial build for an enterprise client is a lightweight proof of concept. A standalone software package that doesn’t have complicated (if any) integrations into current systems. We build it to test if their users/staff want to use such a service and for the company to see the potential reward, before going down the path of time-consuming integrations.

Tell us about your process of designing the conversation flow. Tell us a bit about your team.

Designing the conversation flow, like anything else we do when we build chatbots, is a step by step process.

Our first step is always to define what we call the chatbot’s One True Goal. THE thing the chatbot is there to do, the reason for its existence. What does this chatbot need to do?

Once defined, we go through a user story exercise. During this exercise, we identify all the moving parts, isolating all the users that could interact with the chatbot and what they want from it. It helps us map out each user’s path to the One True Goal.

Finally, now that we have both the chatbot’s One True Goal and a clear understanding of its users, we design the conversation flows. Like anything else in design, we aim to get the user from greeting to achieving the goal in as few steps and as quickly as possible.

Then, once we have nailed this all down, we extrapolate the conversation flow, map out the technical features and APIs the chatbot will need, and we get to work.

We’d like to know your thoughts on the future of chatbots and how their role?

The future is bright for chatbots. Now that we are past the hype and almost out of the disillusion phase, we are heading straight for productivity. Ironically, this gets me hyped.

I believe we will see rapid growth in chatbot usage driven by SMEs.

At the moment, effective chatbot technology remains accessible only to large companies. Little by little, though, the technology will become more accessible. We’ll hit mass adoption within the next couple of years. It will become normal to talk to your local coffee shop’s chatbot.

In the enterprise space, chatbots (conversational software!) will live at the center of the business and across all departments. We are already seeing this happening with our clients.

I do not see any sign of this adoption slowing down any time soon.

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What does ubisend offer to sales and marketing teams?

I see chatbots as a fantastic marketing tool. Marketers are always looking to more effectively engage their audience, reach potential customers, and help them notice their brand. Over the past few years, we have seen a growing awareness of conversations between businesses and potential customers. The lean movement means entrepreneurs no longer build a business in their garage before looking for customers. Today, we all value customer feedback more than anything else.

This trend is spreading into marketing too. Marketing is no longer just about blasting email lists or throwing billboards in front of millions of eyes, hoping a pair of them will buy a product. It is about conversing with the customer, getting to know them, giving a personality to the brand. It is about understanding needs and problems and talking about how your solution is best for them.

Chatbots are the perfect tool to achieve that.

In terms of sales, there is again a lot to be said about a chatbot always being present. It does not sleep, get grumpy or turn up late. The most obvious sales chatbot solution is a tool that sits on an e-commerce website and handles all inquiries. The chatbot knows everything about the catalog of products, makes recommendations, up- and cross-sells 24/7 — at scale.

What is your suggestion for other bot makers? What changes would you like to see in the community currently?

Let’s try to all move away from the word ‘chatbot’, shall we?

What kind of analytics can enterprise look to gain from ubisend’s chatbots?

Much like integrations, analytics are unique to the enterprise we work for.

With every chatbot build, we supply our clients with access to a suite of tools through our ubisend platform. Our platform does not send and receive messages. In it, we log basic analytics (delivery rate, open rate, click rate — the normal stuff) along with advanced reports. Depending on the privacy requirements of the chatbot, a business can watch conversations in real-time, use sentiment analysis and pull out key common questions/problems and issues across every channel.

As we go through the One True Goal exercise with a new client, we map the critical steps we need to measure. From the initiation of the conversation all the way to success, we will track every key interaction. When we ship a chatbot, we also deliver a custom dashboard, specific to the business needs of the client and based on the specific metrics they need to monitor and hit.

Thank you Alexandre! That was fun and hope to see you back on AiThority soon.

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