Chat automation projects’ lifecycle


Over time I’ve noticed a trajectory for companies in adopting virtual assistants. Companies start from any of the starting points and then slowly move up the trajectory as their chat automation project progresses. Needless to say, all the successful chat projects differ in speed but on average, the course is the same.


Understanding this trajectory helps you assess your own organization, where you currently stand and how to think about chat automation in the larger context of automation. Take this as an automation roadmap that you can use internally in strategy meetings or when planning out your activities and budgets for the next quarters. The trajectory goes as follows:


  1. First, companies assess the needs of customer support in terms of volumes of monthly transactions. This is for deciding whether to go for a bot in the first place. We usually advise to use bots if the monthly chats exceed 1,000 conversations. Less than that and you can survive with a human support agent.


  1. Secondly, when companies go for chat automation they do so for certain parts of the customer service channel. The first look is mostly at high volume parts of the customer support. These can be related to certain products or services (e.g. topics related to invoices or billing usually gain the most volume in customer support).


  1. The third step is to offer the support bots across all customer service related topics and perhaps bring in some sales related topics as well. This is done after a pilot when the initial parts of the bot have been tested. Usually there you see that the customer support managers and people leading business development have accepted that the bot can add acceptable value to the organization in the initial pilot phase and the decide for a more comprehensive roll-out of the support solution.


  1. And number four is where things get interesting. What some of the more innovative companies are thinking about are virtual assistants capable of authenticating users. Why is this important? When in the beginning the bots are mostly just giving general advice on topics, then authentication unlocks a lot of powerful features. With authentication, the bot can verify the user’s identity against an internal API and start providing information that previously only a human agent could provide. This can include detailed information about billing, status of ordered services or products, ability to change details related to the account and orders. Essentially anything, that human agent could do for the user or that the user could do in self-service. Yet, with a bot through the chat interface, such queries can be executed faster and in a more convenient manner. Add voice to this and you got a killer combination.


Needless to say, authentication is something we’re offering as well and more on this in the next post. In the meantime, feel free to share this trajectory in-house with your manager to get their buy-in for the automation project you are seeking to push forward 🙂 If you need help, reach out indrek (at) alphablues (dot) com

How To Align Your In-house Team For Executing A Successful Chatbot Project

Like with any project, good planning is the key to success also with your bot project. Having seen many chatbot and virtual customer assistant projects over the past years, there are couple of lessons learned and best practices to keep in mind. The key feature here is how to align your team inside the company so that the project gets delivered in time. The task becomes especially tricky when your company has thousands of employees and you are coordinating tasks across several departments and teams.

Here are the things to help you out.

1️⃣ Pick a leader. Choose the person who is ultimately responsible for the project. Essentially that person is like the “mother” or “father” for the bot. It is his/her task to make sure the project gets delivered. That person is also the one making final decisions on bot related developments.

2️⃣  Choose your success metric. Make sure the team is aligned on what is the ultimate goal of the chatbot you wish to deploy. It can be the number of deflected customer service tickets, increase in response time, saved time for human employees, increased product sales conversion etc. Whatever it is, make sure your whole team knows that is your North Star.

3️⃣ Build in-house or outsource development. Large companies have usually in-house developers that could be capable of building chat automation systems. If you have such teams at your disposal then it is possible to get started there. However, in many cases such teams have plenty of things to do and usually it is easier to run first chat automation pilots with an external developer at smaller scale to see their capability and also measure how well chat automation can help your company.

4️⃣  Have your team be ready for the long term. Understand that your bot is not perfect on day 1. It takes a few weeks first to see how well the bot is performing. In next iterations which take another few weeks you can start measuring how people respond and what are the things you need to change. It can take a few months to get a good picture of how best to optimize your bot so get your team ready to be in it for a few months to really see the results.

What I recommend you to do is communicate this to your team beforehand. It will make the project less turbulent and you are more likely to maximize the value of your invested time and effort. And if you need help with these decisions, then reach out indrek (at) alphablues (dot) com and I can provide some quick insight and second opinion.

New customer – Enefit

Glad to announce that Enefit has launched their virtual sales assistant on the Finnish market. Enefit is Eesti Energia’s subsidiary in Finland. Eesti Energia is an energy group which consists of more than 20 companies and employs approximately 5 800 people. It is the largest producer of energy in the Baltics, incl. one of the biggest renewable energy producers. Enefit is currently in Latvia, Lithuania, Poland, Finland and Sweden.

Enefit recently entered the Finnish market and built a virtual sales assistant, called Sähköbotti (Energy Bot in Finnish). The bot was built on the AlphaBlues platform and integrated on the website. The bot helps new customers choose the best energy package right from the website.

Enefit chose the bot to differentiate from the competition and offer its customers new and easier ways of purchasing energy plans. As the energy markets are highly competitive, such differentiation helps Enefit stand out with its digital and user-friendly customer experiences.

#AI and #fintech Demo Days with Polish corporations

At the beginning of the year we joined the PwC Startup Collider program in Warsaw Poland as our first steps into that market. From our company point of view the past few weeks have been exceptionally exciting as we have been able to attend several corporate-startup matchmaking events in Poland and met with a large variety of companies to understand their needs when it comes to AI and automation.

In mid-March we attended The Heart Demo Day at the awesome Warsaw Spire building. The Heart is a leading corporate-startup matchmaking incubator in Eastern Europe and this demo day was focused on marketing and communications related startups. The level of the participants was high as most startups were more mature and some having raised already multi-million dollar funding rounds. Was great to see companies pitch their products and really emphasize their use cases with existing customers. In the B2B world, use cases and references are everything.

Indrek pitching at the demo day to Polish corporations.

In addition we attended at the end of Marh the ING Bank startup demo day at their Polish headquarters. ING has setup an Innovation Lab at their HQ and the event was focused on startups in the AI and fintech space. The lab is run by a great team of innovation professionals. Startups were again of high quality and it was a great example of how large corporations are really doing focused innovation work with technology players in the market.

With the ING Innovation Lab team that made the Demo Day possible.


5 Things Successful Companies Do When Setting Up Their Virtual Assistant

You’ve become interested in having a virtual assistant for your company but are unsure how to start. What should be done? How? What is important? What is less important?

These are all questions we get when we meet with companies. They wish to know what is the best practice in setting up a bot and what to keep in mind. Having deployed dozens of bots we have a learned a thing or two and we’ve highlighted some of the key lessons to keep in mind below.

Each of them deserves more attention than we can give in this short post and I’ll follow-up in the next posts with more insight into them.

That being said, here are the key things to decide and keep in mind when thinking of setting up a bot:

1️⃣ – Pick a use case for your bot. Is it customer service? Is it selling products online? Build a case what is that you want to achieve with the bot? Many want to offer a 24/7 channel for customers to get in touch or make their staff more efficient or understand what customers actually want to know about your company. All are good things to consider a bot. Pick yours.

2️⃣ – Where do you wish to put your bot? A good option is to put the bot on your website inside a chat window. Another is to implement in Facebook Messenger. Or if you have a mobile app, you can include it there as well. Consider where do you currently have customer traffic coming in and pick that channel.

3️⃣ – Pick your language. It is easiest to start to have the bot in one language. If your website is in English then train a bot in English. If your website is in Latvian and Russian then pick the language that gets used the most. When you start out with one language you can learn how users interact with your bot and you then take these lessons to your next iterations. If, however, two languages are crucial, then include both bots in the same channel through language detection.

4️⃣ – Automate the 20% of user questions that give you 80% of volume. Automation with chatbots is all about getting the most value out of volumes. Go for the low hanging fruits. The questions and issues that hundreds and thousands of your customers have. These are also the questions that take most of the time for your colleagues to answer. Or if you run a sales bot on your website, build it so to respond to the most common questions about a certain product or topic.

5️⃣ – Have bot-to-human handoff available. Bot cannot solve everything all the time. Humans are still needed in the process. Make sure your bot is capable of directing unanswered questions to humans for follow-up. Alternatively build your bot so that it is capable of giving people directions how to get in touch with human support.

There you have it. 5 things that you need to keep in mind when starting a bot project. Make sure your whole team understands these topics when you get started with your bot project and ask your tech provider about these topics.

Resolving them early on will make your project better and more likely to result in positive outcome. If you have questions, reach out 👉 indrek (at) alphablues (.) com and we’ll get back to you in 24 hours to offer our feedback.

New product release: speech-to-text and text-to-speech integration

Excited to announce our latest product release as we integrated speech-to-text and text-to-speech functionality into our product. Now it is possible to add voice recognition into our virtual assistants so that your users can speak directly with assistant and get answers without the need to type. This opens up a wide range of possibilities such as:

  • Integrating voice input based virtual assistants on your website directly from the chat window with the push of a button.
  • Utilizing speech based input from your mobile app in customer service. You customers don’t need to type questions and can simply speak to the chat window.
  • Ability to transcribe existing phone call logs and use that data automatically in training your customer service systems.
  • Using text-to-speech to have the assistant read out answers either on the website or in the mobile app.
  • Building a “customized Siri” that can be integrated also into a hardware device 🙂 For example if you are a telco and want to have voice guided functionality in your TV remote control.

The opportunities are really endless as voice based interfaces with machines get smarter and become more available during 2018 and beyond. There are more than 47 million people reached by smart speakers (predominantly Google Home and Amazon Echo) in the US already. This goes to show that consumer adoption of the devices is already at a strong level.

What is needed next are consumer facing products and service that utilize voice in a smart manner to provide value for users. With any technology it takes time for the capabilities to mature but considering the quick uptake of these devices by users it is evident that market demand is there. Now it is a matter of satisfying that demand with relevant offerings. Reach out (indrek.vainu @ if you’re also excited about voice and want to delight your customers.


We also gave an interview to a news portal on where NLP is headed and what role voice plays in such developments (in Estonian)

All You Need To Know About The Technical Side of Natural Language Processing in Chat Automation

We often get asked how does NLP work in chat automation.

What languages is it good at?

Does it really understand my language?

What algorithms do you use in your pipeline?

To accommodate those requests, we added this video where our CTO Hendrik talks about these topics at the Nordic Data Science and Machine Learning Summit in Stockholm. It is a technical presentation and gives a good overview of how machines understand language and how we approach the topic.

3 Reasons Why You Need A Bot And 1 Reason Why You Don’t


One of the questions that we encounter when talking to people at trade shows and tech conferences is “Why do I need a bot?”. It is a valid question. Why indeed.

Bots have been around for almost 2 years now if we count Facebook’s opening of the Messenger API as the day when it started in large scale. Since then there has been plenty of experimentation and developments. By and large we see 3 reasons why customers need a bot. I’ve also added 1 reason why they don’t need a bot in the end to keep a nice balance 😁

1️⃣ Your customers expect you to answer immediately whenever they require something. Yeah, I know. You are expected to be online 24/7 waiting for your customers to get in touch. Sounds like a lot of work. And it is. But this is the new reality what customers expect. With the advent of always on services, customer expectations have grown. A lot. They expect you to be there for them when they have questions and are annoyed when your company cannot be reached. Nobody likes waiting in phone support queues and with basic chat automation you can tell people that you are working on their issue. Already this eases your customers’ mind as they know that somebody in the company is working on their issue.

2️⃣ Just look at the data. Chat conversations have grown tremendously over the past years. Customer service messaging company Intercom has reported that close to 400 million conversations have been started using their messaging system in 2016, compared to just 190 million in 2015. Messaging is a powerful medium and the popularity of WhatsApp and Facebook Messenger feed this trend even more.



3️⃣ It is very likely that your customer support cost are slowly eroding your profitability. Maintaining human workforce to respond 24/7 to thousands of customer request coming in online is expensive. This is especially true to companies selling digital products. As they experience growth, the pressure on customer interaction automatization grows because to handle growing volumes in customer service tickets, the companies need more employees. It is not uncommon to see ⅓ of certain companies workforce be employed in customer service. Here is where automation can help you scale your business without scaling your cost base.

And here is 1 reason why not to do a bot – We’re also honest in recommending a bot for our customers and the one case where we do not really recommend it is when you have less than 1,000 incoming customer chats per month. The reason is that such volume can be handled by a human relatively well. Those roughly 32 chats per day can be answered by a human and in such cases using AI and bots might be a bit of an overkill.

With that I encourage you to look around in your organization at the various touch points you have with your customers. Talk to customer service people and digital marketing folks. Understand whether there are any bottlenecks where automation can make your employees and company more efficient. If get stuck, don’t worry, happens to the best of us. Get in touch (or talk to our bot on the right 👉) and we can share specific advice to help your case.

Deep Learning Summit San Francisco recap

We’ve been travelling quite a bit the beginning of this year. One of the best events thus-far has been the Re-Work Deep Learning and AI Assistant Summit that took place in San Francisco in January 2018. It hosted a variety of exhibitors (including AlphaBlues 👍) and close to 1,000 participants. The talks were of high quality and there were several interesting exhibiting companies. I put down some thoughts that we observed throughout the whole trip in Silicon Valley as they reflect the state of the AI in the NLP & intent understanding space that we are working in.

  • There were plenty of tech talks from highly technical people but the underlying impression was that majority of the tech is still in research phase when it comes to understanding conversational dialogue. It is a tough problem mainly because of the limitation that we currently have in context understanding. There are approaches focusing on previous steps in the dialogues but a common theme from the talks was that the lack of labelled training data is a major bottleneck.


  • Several large tech companies are now in the voice assistant game with their home control devices. Voice is an upcoming trend and as Google, Amazon and Apple fight for the prime spot in the living room, understanding meaning from voice becomes important. Large companies get billions of queries each month (that is some sizeable training data) and it can be understood how with more and more use, they come in possession of the largest training sets. And as such can improve their systems the best.


  • NLU is not only limited to understanding real-time human-machine communication but also used in searching through logs of messaging content in team collaboration tools. This is an interesting angle as there is ton of message based content left behind in various workplace tools (i.e. Slack). Make those queries intelligently requires the understanding of meaning in messages and can help in information retrieval.

    At the expo with the always helpful Re-Work team member.

AlphaBlues partners with PwC

PwC Startup Collider has chosen 12 technological startups from the European region and happy to announce AlphaBlues is one of them. The companies were selected out of 300 applicants to partner with PwC in Poland to expand their product offering in Central Europe. “As part of the Startup Collider, we are looking for innovative startups that will become our business partners with whom we will really develop a new joint product” says Beata Cichocka-Tylman, PwC’s Director responsible for innovation and R&D. During the process AlphaBlues will receive support in business development and an opportunity for international expansion alongside one of the strongest global brands. More details are available at this link