In 2019, the percentage of companies using CRM systems rose to 74%, while the percentage of websites using chatbots is, based on my talks with customers, still below 10%. So, barring some kind of weird anti-trend, most companies that use chatbots probably use CRM systems, but not many companies that use CRM systems also use chatbots.

However, I am confident that the two will end up being used together in the future — we aren’t at this level of perfect synergy quite yet, but there are already several reasons why bots love CRM (and vice versa). At Solvemate, we’ve successfully…

Needless to say, we are living through uncertain times. How the months ahead go will depend a lot on our actions as individuals, as companies, and as nations. The pace of technology has fortunately brought us new ways to communicate with each other and keep touch with each other. But while texting your friends or Skyping with your loved ones is almost second-nature to many of us, those of us lucky enough to continue more or less “business-as-usual” from our remote offices have a tricky type of communication to master — electronic business communication.

Not to say that electronic communication…


Two years ago, I wrote my first draft of a chatbot taxonomy. My goal was to establish a common framework that could be used to identify different kinds of chatbots, shedding light onto what was then a brand-new technology.

Years later, the market has matured — as has our understanding of it. The scene is no longer one in which newly-founded vendors play “buzzword bingo” with inexperienced customers. In a market where chatbots are commonplace, customers no longer care whether vendors are selling them an NLP-AI-ML-Big-Data package. What they care about are results. …


Throughout 2019, I’ve shared my thoughts on more than a few topics around the future of customer service — everything from why E-mail, Phone, and Helpcenters will all fall out of favour (they are all inferior interfaces — slower, less mobile-friendly, and/or asynchronous — compared to text chat) to The Human Adaptability Problem (the idea that technological advancement is outpacing our ability to learn).

Now that we are wrapping up the decade, I wanted to give a synthesis of these thoughts, digesting them to identify megatrends and to paint a vivid picture of what customer service in 2025 could (or…


Business leaders often say things like “we are a data driven company” or “we take decisions based on data”. This is a good mantra in principle. But “being data driven” is about more than adding it to a list of company values. Data needs to be done right.

Let’s go through the typical scenario of “data-driven decision making.” There is a meeting room with a big display TV at the front. Someone pulls up a chart showing a key business metric before and after a project was launched; revenue before and after a big ad campaign, for example. The…

Mary Meeker has released a yearly Internet Trend Report every year since 1995. Her analyses are always interesting and insightful, but this year’s report in particular contained a slide that has stuck with me.

I am talking about Slide 157, which includes a chart that looks something like this:

Technology changes surpassing human adaptability? What is this nonsense! We are the most adaptable animal on the planet, after all! We can go anywhere, do anything!

We are indeed impressive beings. But therein lies the problem — we are so amazing that we are creating technology faster than we ourselves can…

Neither rule-based nor algorithmic chatbots are a silver bullet. Each of them has certain use cases where they are strong, and others where they fall short. Here, I will explain the difference between the two and share my theories on when we should use which type of bot.

Rules = Explicit programming

In this article I have used explicit programming as the key differentiator between rule-based and dynamic flow generation. This means that the bot does exactly what has been programmed by a human. These are mostly “nested if-then rules”.

Problems with explicit programming:

  • Limited human mental capacities: if complexity grows, humans cannot handle…

At Solvemate we have built a software where our customers can create chatbots to automate customer service. Our bots deal exclusively with messaging interfaces such as chat widgets and Facebook Messenger. We do not support voice.

Quite often I get asked — “why?” Calling has been around since 1876; a phone number is an extremely common gateway to get help with everything from restaurant reservations to flight bookings; and nowadays bots like Alexa and Google Home are giving us even more ways to use our voice to get things done. If we support messaging, shouldn’t we should support voice…

The situation

All businesses are under pressure to keep processes lean and costs low. That means expensive customer service is fundamentally problematic: Serving thousands of customers creates an immense pressure for support agents to be efficient. No wonder they often sound stressed on the phone.

Today, I want to take an in-depth look at that problem and propose a way to solve it. I’ll calculate the cost drivers of providing customer service and show you just how expensive it gets.

High operating costs

First, let’s see how much it actually costs to operate a customer service team. …

We live now in an instant economy, where as societies, we expect to get everything on demand. It’s almost a daily reality, where products appear on our doorstep within 24 hours and the newest episodes of our favourite series are just a click of a button away. The shift has of course not been immediate, but has started already decades ago when we moved from analogue to digital, moving to the rapid growth of the internet, smartphones and social media. Through the decades of development, each industry in their turn has tried to adopt.

The big winners of this change…

Erik Pfannmöller

CEO @ Passionate about AI, computers and software. Like structure and efficiency. Nerdy on details. Love keyboard shortcuts. Chasing a big vision.

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