Chatbot survey 2020 "post Corona" - Download by Sophie Hundertmark

The word chatbots is on everyone’s lips. More and more companies are relying on a digital assistant in everyday life. But when did many companies start working so intensively with chatbots?

For which use case is the chatbot used in the company and how has demand changed due to coronavirus?
How do users react to the company’s chatbot?
And very importantly, where do respondents currently see the biggest problems in their chatbot project?

I tried to find out these and many other questions in my current chatbot study. The survey took place in the DACH region in November (2020). Around 50 people from different sectors and company sizes took part.

The results are interesting. They offer a lot of potential for the more targeted optimization of chatbots and at the same time raise new questions.

The most important facts summarized here:

The majority of respondents (34.3%) have only been using a chatbot in their company since this year. Last year is in second place with 22.9%. In addition, there are still almost 10% of respondents who do not use a chatbot in their company at all. So the good news is that over 90% do!

One of the most exciting questions is certainly what the respondents use the bot for in their company. The customer service bot (57.1%) leads by a clear margin ahead of marketing (28.6%) as a use case. The ranking is completed by the use cases internal for employees, triage of live chat, recruiting and IT helpdesk, which all achieved 14.3%.

Due to the current situation, the companies were also asked whether the need for a chatbot had increased as a result of coronavirus. Almost two thirds of those surveyed stated that coronavirus had not led to an increase in demand. This answer seems quite surprising when you consider that digital communication channels are increasingly being used in times of coronavirus.

When it comes to the size of project teams for chatbots, companies are still rather cautious. Almost 90% have so far relied on project teams comprising a maximum of 10 people. Almost 50% of these are project teams with a maximum of 3 employees. In contrast, only 5.1% of the companies surveyed implement larger project teams with more than 20 participants. So there is still plenty of room for improvement here.

The question of budget is also interesting. Two extremes are emerging here. While 48.7% invested less than EUR 5,000 in their chatbot in 2020, 25.6% of companies stated that they had invested more than EUR 40,000. The rest of the respondents are therefore in between. This large divergence is probably due to the different types of chatbots used (see Figure 8). While AI-based bots can quickly cost several thousand euros, rule-based chatbots are usually much cheaper.

And what about the satisfaction of your own chatbot? Here, 77.1% of companies stated that they were satisfied, but also saw potential for optimization. As many as 14.3% of companies are perfectly happy with their chatbot, whereas 8.6% are not yet convinced by their own chatbot. The good news is that none of the companies surveyed have stopped the chatbot project so far.

Users are almost as satisfied with their chatbot as the companies themselves. 74.3% of the companies surveyed stated that their users are open to chatbots. While 22.9% are skeptical, only 5.1% reject the chatbot outright.

As previously mentioned, the proportion of companies that use an AI-based chatbot is just over half (54.3%). As a result, 45.7% of companies currently still rely on a rule-based chatbot. However, these are often completely sufficient for the start and you can expand your chatbot project step by step, because as already described, AI-based bots can quickly cost tens of thousands of euros.

And what is the biggest problem when it comes to a company’s own chatbot project? Here, more than half of the companies (51.4%) see too few internal resources as an obstacle. In addition, the lack of acceptance by users (17.1%) and a lack of knowledge and acceptance internally (12.8%) are also seen as a problem. The lack of budget (8.6%), the still immature technology (8.6%) and the wrong choice of chatbot provider (5.1%) were described as less problematic.

The survey comprises a good 12 questions and can be ordered directly here. Please fill out the following form.

Of course, I would also be happy to support you personally with your next chatbot.
Whether it’s use case finding, design, personality definition, optimization, bot dialog writing, defining your suitable chatbot personality or dialog design – I’m happy to help.
Either we do everything together or I simply offer help to get started or give feedback afterwards.
The best way to do this is to book a consultation with me. You can choose a date from my calendar right here.

... Sometimes time is money.