Chatbots and automated assistants can take on many use cases and be deployed into a number of different platforms to support your customers.

They can be integrated into any platforms such as website, Facebook Messenger, WhatsApp, Slack, Microsoft Teams.

Lets look at how chatbots can be used for sports events

As chatbots have become more powerful this has enabled them to take on more complex roles. Using chatbots for sports events can provide an effective tool for mass participation events organisers, sports clubs, race promoters and charity event coordinators to handle participant enquiries 24/7, aid in event organisation and provide an effective marketing tool for event promotion.

Advancements in conversational UIs and AI in sports events management may not be as fast and impactful yet as in some other sectors, but these technologies have the potential to redefine participant experiences and enable smarter event management for the organisers.

Whether you organise Triathlons, Cycling, Swimming, Running or Motorsports events, we are going to cover 6 of the reasons why you should be employing chatbots to support your event.

Chatbots for sports events- Chatbot to support your triathlono

1Familiar Technology

These days sportive, triathlon, marathon participants and entrants are savvier and demand an intuitive and seamless customer experience, using technology to fit in with their communication habits.

Every day 1.4 billion people around the world send over 50 billion messages to communicate with each other. Many prefer social media and mobile platforms for communication and expect organisers to be on-line when they are.

If users are having a conversation with a chatbot in Facebook Messenger, they are using a conversation channel they are familiar with and they are already using the technology and don’t need to install a new app. The numbers of messenger app users have been steadily rising. 2 billion messages are sent on Messenger every month (Facebook data, January 2018).

 

 

Chatbots for sports events-Chatbot to support your sporting event, improve participant conversation

 

2Improve Participant Communication

Event organisers can struggle to provide easy contact points to participants, event attendees are often dogged by problems with contacting anyone running the event.  Traditional channels such as email and organic posts on websites and social media are not performing well enough to rely on completely.  Using chatbots for sports events provides the perfect tool for organisers to send and receive information to/from their entrants.

A chatbot can enter into personalized and automated communication with entrants pre and post event. Using push notifications to send new event information or gaining valuable entrant feedback for post-event evaluation.
Using these techniques a chatbot is able to reach participants wherever they are, regardless of where the chat session was initiated, whether on a mobile app, a website and even from social platforms such as Facebook Messenger.

As a result of using this, a chatbot can be an ideal tool for last-minute event notifications to be broadcast to participants, ensuring that entrants receive the information on time and when it’s relevant. Your event chatbot can also be programmed to respond to users requests to speak to event organisers so that users are always able to converse with real people if needed, ensuring the optimal customer experience.

Chatbots for sports events-Chatbot to support your running event

3Provide Fast Event Information

From an event participants point of view, as we all know, the morning of an event can be stressful and this is often the time when participants need to get to event information as quickly as possible.
Participants spend months training, meticulously buying the correct gear and hours pouring over their training stats and their training routine but it’s surprising how often they forget about the more simple things:

  • “What time is the event parking open?”
  • “what do I need to bring for registration tomorrow?”
  • “does the shop at the event start sell inner tubes?”

A chatbot gives them an easy way to get the right event information fast.
Entrants may still have questions that an event website itself does not answer or does not answer quickly enough. Entrants often find it easier to ask than to search a website. In that case, the chatbot acts as a super navigation assistant to the current information. With AI working in the background the ability to train a chatbot means that the information it provides is always relevant and up to date:

  • what food is available at the feed stations do you know if they provide gels, I’ve forgotten mine?
  • “I’m in Wave 2 what time do I set off?”
  • “whats the water temperature like, do I need to wear a wetsuit today?”
  • “At what distance is the first feed station?”
  • “you won’t believe this but I’ve forgotten my spds can I buy any at the event start?” Sounds far-fetched but it does happen!

For organisers, this gives them peace of mind that entrants have all the required information as well as reducing the costs involved in dealing with each individual enquiry.

The real challenge is building natural language technology that supports the range of questions that entrants ask — for example, all the different ways that people might ask whether they can use tri-bars: The Aktivebot smart automated events assistant can help here.

Chatbots for sports events-Chatbot to support your triathlon event

4Multi Language Customer Support 24/7

For event organisers, the biggest challenge to serving your customers in several communication channels is responding quickly on the run-up to an event and on the event day itself. Although a chatbot cannot handle all customer queries, it can be used to deal with many of the routine event queries that typically make up most enquiries.
One of the great benefits of a chatbot is the constant availability. Customer expectations are high and event participants are no different in expecting a quick response to enquiries. Particularly when it’s race or event day it becomes vital to provide the relevant information at any time of the day.
With a chatbot, you can offer your entrants a customer service which is available 24 hours a day even when there are no employees in the office. You can rely on your bot no matter what time of the day or day of the week or timezone the enquiry is coming from.

Chatbots can be enabled to understand multiple languages. This can be very useful if you are organising global sporting events and want to be able to answer all your entrants without the costs of employing multilingual customer support.

Chatbots are scalable and capable of handling multiple enquiries at any one time, ready to step up when event day enquiry demands are at their peak.
A chatbot can give organisers the ability to have more conversations and help more people at once than other alternatives, for example, live chat applications on websites.

This ability to handle the frequent enquires where the responses are often similar facilitates organisers in freeing up event staff to deal with the more complex issues

Chatbots for sports events- Chatbot to support your cycling event

5Results and Entrant Data Integration

Event registration, deferment and results processes can still be a headache for many events organisers. Difficulties for entrants contacting organisers about their places can often cause them to look elsewhere and this is a sure fire way to create a loss of confidence in your sports event.

With the correct integration development, a chatbot is able to answer complex enquiries by integrating with existing event registration and participant management solutions to immediately look up the correct information. For example, a participant enquiry asking to defer their place due to injury can be actioned and a refund provided easily.
A chatbot can also provide information about event availability and direct entrants to alternative options if there are no places.
Event results are an important part of sporting events. Chatbots can integrate with your results data systems to provide participants with an easy way to look up their results. Chatbots can also be used to notify participants when their results are available via opt-in notifications.
Using chatbots for sports events enables you to connect your chatbot seamlessly with your entire event ecosystem- CRM, ERP, CMS, and other key events applications.

chatbots for sports events - Messenger Marketing, using a Chatbot to promote your event

 

6Events Promotion Using Facebook Messenger Marketing

There is a lot of competition for events companies these days. Sporting events happen on a daily basis meaning the choice for triathlons, sportives and marathons almost seem endless.
With all the noise and excitement competing for attendees, it’s imperative that your event stands out. Your event needs to ensure it’s the one that people repeatedly flock to ensuring a good turn out of entrants and supporters.

Using a chatbot for messenger marketing can help to achieve this.

Traditional ways of promoting events are becoming less effective. Email marketing rates have 5-10% open rates, FB news feeds 0-1% visibility and mobile conversion rates flagging at 1-2%.
In contract through a chatbot opt-in targeted messages or push notifications in Facebook Messenger have up to 90% read rates and a 40% click-through rate.

Event organisers can leverage messenger marketing  to:

  • Promote new events
  • Create noise for your sponsors
  • Request valuable participant feedback
  • Provide training suggestions
  • Drive fundraising

Creating a Buzz For Entrants and Supporters

One of the reasons we love sports events is the anticipation, in the run-up to the event itself, waking up on the day of an event with a spring in our step, and then the palpable rush when we reach the start itself,  checking our gear and attaching our rider/runner number. As an outdoor events promoter, building the hype is an important task ahead of mass participation events; this is not just to build entrants excitement, but to sell places and secure a healthy return on investment.

Maximise Sponsorship Exposure At Your Event

Sponsors are a vital part of an event.  Using Messenger marketing to provide exposure to your sponsors ensures they get max ROI and helps to gain new sponsors in the future. If you’re in it for the long-haul, and plan on running your event many more times in the future, then it’s worth keeping all of your current and potential sponsors engaged.

Conclusion

These are just 6 reasons we’ve covered

Chatbots for sports events-Support your mountain bike eventIt’s clear that using chatbots for sports events is an ideal tool to add to your event management toolbox. Chatbots can significantly improve entrant satisfaction and provides the ideal promotional tool to grow and ensure your events run smoothly at maximum attendance.

Feel free to comment if can think of any other reasons to use a chatbot to support your sports event.

Read More: Learn How AI Powered Sports Software Helped Event Organisers

 

A Sports Software Chatbot Case Study: The Fred Whitton Challenge Sportive automated assistant, advanced

We report on our AI chatbot sports software project to aid the organisers of one of the UK’s most well-known cycling events.

 

Leverageing ai powered sports software with our core Aktivebot chatbot the goal was to create an automated assistant available 24/7 to reduce time and effort needed by event organisers to respond to event enquiries whilst still providing an easy way to contact the events team if necessary.

The Saddleback Fred Whitton Challenge is a charity event in honour of the late Fred Whitton consisting of a 112-mile charity sportive around the Lake District and is arguably one of the UK’s most well known and hardest sportives with over 2000 riders and 5000 applications this year.

 

 

The chatbot sports software was used by organisers to cover the event

The Fred Whitton Challenge has been running since 1999 and as a result is extremely popular with over 4000 followers on their Facebook page where a large number of ride questions were being asked via the message me button there. We wanted the AI chatbot to assist the event organisers in answering ride and registration queries and reduce the amount of time spent answering routine questions. We also wanted to provide the ability for users to look up their time for this year and previous years.

The chatbot we created is integrated within the “Facebook Messenger app” of the Fred Whitton page and users can contact it through the private “Messages” feature of their page, or directly through the Messenger App.

The sports software project

The project brief was for The Bot Forge to create an AI powered chatbot capable of handling event enquiries 24/7 which could be deployed into the Facebook Messenger framework and utilise rich ui elements. Future deployments could be aimed at website integration.

For such a long-running event, Human Race and the Fred Whitton organisers wanted to provide the optimum user experience and still make it easy for participants to message organisers directly through the chatbot if they wanted to contact a real person by messaging them directly.

The chatbot understands human language, leveraging advanced Natural Language Processing and answers questions such as “what is the fred whitton?”, “ I’ve injured myself at the weekend I need to defer till next year”,“ when can I get my race pack?”, “ help I need the GPS files for the route”, “ Is there any way to buy a jersey post-event?”,”I want to contact an organiser”, and “when will the results be available?” The chatbot replies to a question based on it’s own programmed data or points to the specific information on the Fred Whitton Website so that it works in tandem with the website itself.

Press the play button to watch a real conversation with The Fred Whitton Chatbot

The technology

We used Google Dialogflow to provide the NLP engine and Google Firebase for the fulfilment hosting. The fulfilment or web-hook is where we were able to compute more complex answers for the AI chatbot to give to users and create the correct responses for. For example when looking up users past ride times, the web-hook was able to look up past results for users from a results database. Facebook ui elements added rich content, particularly useful when asked about merchandise details and availability; linking directly through to the official shop.

The conversations

The real challenge in creating the chatbot was leveraging natural language technology that can support the range of questions that event participants might ask: for example, all the different ways that people might ask about the route. We are helped in this process by our own Aktivebot pre-created sports events intents.

Small talk

The chatbot includes the ability to provide small talk, which is used to provide responses to casual conversation. This feature greatly improved user experience when talking to the agent.

Initial question data

Initially, we imported the pre-created sports events intents (an intent represents a mapping between what a user says and what action should be taken by the chatbot).

We then looked at FAQ data provided by the Fred Whitton steering committee and historical questions to their facebook page which gave us some invaluable insight. Using this information we were able to create the conversational scripts and then implement the conversation ability with each question matching an intent

This was an iterative process. Matching user intents to core functionality and features and training the natural language processor to understand users and handle conversation failure scenarios gracefully.

The conversational UI was then fine-tuned, with rich elements implemented where necessary.

What were the questions?

Most asked questions by participants match the questions that the event chatbot is able to answer, i.e.:

  • Questions about registration: deferring places, available places, waiting list enquiries.
  • Questions regarding merchandise: jerseys for sale on the day.
  • Questions about the ride: route details, information about closed roads, clothing enquiries.
  • Questions after the event: results, photos availability, the next ride date.
Sports Software Chatbot- Top Intents handled by conversational agent

Top Intents handled by the conversational agent

The training

The questions were often related to ride specific information. This meant that for an optimal intent matching rate, it was necessary to work closely with the event organisers to provide answers to specific questions. The capabilities of an ai sports software chatbot will improve over time, the more messaging transcript data the better so the more it’s used the better and more accurate it will get. Hence the training logs were checked multiple times a day and improvements made where necessary. By focusing on all questions answered it is possible to greatly improve the intent matching rate of the chatbot over time.

The training data was invaluable for perfecting the bot conversations. The process highlights any need for new responses as a continuous cycle of continuous learning.

The “training” of the chatbot can then be used from one year to the next. Any event detail changes can be carried out easily.

Results

The sports software chatbot was launched on 21st March with the scope constrained to Facebook Messenger with no advertising whilst the chatbot was evaluated.

Activity

The high number of participants using the chatbot can be explained by the fact that visitors still have questions that the website itself does not answer or does not answer quickly enough. The chatbot was, therefore, a great place to provide up to the minute event information, such as information about closed roads and the slight route change which resulted in one more hill showing.

The chatbot was not heavily advertised so we envisage activity levels will improve as participants get used to the chatbot as a resource they can use and other strategies to engage users are utilised.

The chatbot was answering questions on the run-up to the event and also during and after.

Success rate

The success rate of the chatbot to answer queries was overall around 60%. With more focused training over a longer period with another event in 2019 we expect this figure to rise until our aim of an 80% success rate is reached.

Sports Software Chatbot Success Rate Over the Past 30 days,

Chatbot Success Rate Over the Past 30 days

Feedback

The chatbot worked well in Facebook Messenger as its one of the preferred channels for chatbots in general. Deploying the chatbot in a chat widget as part of the website itself would undoubtedly result in more engagement and something to consider for the future.

Help intents and the handover protocol were also very successful. If a user did not get a correct response and/or wanted to get help or contact an organiser directly this worked really well. The overall feedback from users was positive. There were always some intents which the bot would struggle to match the first time which would be handled gracefully; however, due to the ability to train the chatbot, leveraging AI the correct response would be prepared for next time.

I’m impressed with the chatbot it seemed to work well. I think it is a good source of help and with it learning as it goes along it would answer lots of questions going forward. If it cannot help it still contacts the organisers where we can answer.

Carolyn Brown: Fred Whitton Challenge Steering Group — Saddleback Fred Whitton Challenge

The Fred Whitton Challenge chatbot still has many areas where it can be developed and improved, particularly by providing more integration with existing systems and utilising push notifications: this will be something carried out in the future.

Overall the success of the chatbot hightlights the benefits of deploying this type of ai sports software in sporting events and is definitely something to consider to give event organisers an advantage in a competitive market

INBUSINESS COVERS OUR AI CHATBOT IN SCIENCE AND TECHNOLOGY SPOTLIGHT

It was great to have our AI Chatbot featured in the inBusiness magazine issue spotlight this month. You can read the feature here 

inbusiness ai chatbot article

Image: https://chambermk.co.uk/profile/inbusiness

Inbusiness is a bi-monthly publication and digital magazine created by distributed to over 3,000 business contacts in and around Milton Keynes. The June/July 2018 issue spotlight was science and technology so it was great that the editors of the magazine wanted to cover our Fred Whitton Challenge ai chatbot, particularly when the ai chatbot was created to assist the organisers of a charity ride.

You can learn more about our chatbot agency here.

We also cover further technical details about the project here.

ONSTAGE AT I/O 2018 Showcasing Google Assistant

GOOGLE HAS STARTED OFF ITS ANNUAL 3 DAY I/O DEVELOPER CONFERENCE AT SHORELINE AMPHITHEATER IN MOUNTAIN VIEW, CALIFORNIA. 

In the first day, they have shown some of the amazing new capabilities of Google Assistant. One of them is being able to make phone calls on your behalf. You ask Google Assistant to make an appointment and it makes the call in the background. The demo has to be seen to be believed.

CEO Sundar Pichai played back a phone call recording that he said was placed by the Assistant to a hair salon to book an appointment.

With a voice which sounded totally natural; the person at the salon had no idea they were talking to an automated AI assistant. The Assistant even managed some small talk; dropping “mmhmmm” into the conversation.

Pichai reiterated that this was a real call using Assistant and not some staged demo. “The amazing thing is that Assistant can actually understand the nuances of conversation,” he said. “We’ve been working on this technology for many years. It’s called Google Duplex.” Pichai also made the point that Duplex was still under development and that Google plans to conduct early testing of Duplex inside Assistant this summer. Their aim is “The technology is directed towards completing specific tasks, such as scheduling certain types of appointments”

Google has a blog post with more Duplex information here which has a lot more examples of Duplex in action using different voices, for example, a really interesting one making a call to a restaurant to book a table.

Google again states that these are real-world examples.:

“While sounding natural, these and other examples are conversations between a fully automatic computer system and real businesses.”

This post also does a good job of highlighting some of the real complexities of having a conversation successfully. With many sentences having different meanings depending on the current context. In the same conversation early on the assistant also handles misinterpretation when the person called mentions a table number taken from what she has misheard. Google Assistant seems to handle this perfectly.

This looks set to be groundbreaking technology:

For users, Google Duplex is making supported tasks easier. Instead of making a phone call, the user simply interacts with the Google Assistant, and the call happens completely in the background without any user involvement.

We are looking forward to seeing more of it in summer and using the technology in our projects.

With Google also announcing their rebranding of its Google Research division to Google AI. The move shows how Google has increasingly focused R&D on natural language processing and neural networks.

It looks like Google are setting their sights on being the world’s biggest artificial intelligence (AI) company. 

In the wake of the Cambridge Analytica scandal Facebook announced late in March that it was pausing its app review process, which meant developers were no longer able to launch new apps or chatbots on the Facebook ecosystem.
It was an abrupt halt and although temporary was not ideal for any developers planning to unleash a shiny new Facebook Messenger chatbot into the wild. We were lucky ourselves that we had got one of our own bots The Fred Whitton Challenge Chatbot live a few days earlier

True to their word the pause has only been a few weeks so its great news to hear that Facebook has re-enabled the app review process so that new chatbots can now be connected to pages and set live.

App Review is Back

Today we are re-opening our app review process. The process has changed a bit as we now require business verification for apps that need access to specialized APIs or extended Login permissions. Apps that ask for basic public profile or additional permissions, such as birthday or user friends, are not subject to business verification.

 

You can read Facebook’s official statement here.

The point has to be made however that this is a helpful reminder to not be reliant on a single platform. Particularly as Facebook has a habit of changing things. Facebook executives Campbell Brown and Adam Mosseri have also stressed the idea that publishers, at least, should not be too tied to Facebook while speaking at Recode’s Code Media conference. If users find the whole experience too unsettling then Facebooks answer is “If anyone feels that this isn’t the right platform for them, then they should not be on Facebook,” Brown told Recode.

Here at The Bot Forge its good news and we are pleased to be able to get cracking building some fantastic new bots.

Conversational AI Terminology Cheatsheet

Conversational AI technology is not new, but the advanced in the technology has driven a major growth in the industry and what can be achieved in its role solving business problems for many types of industries.

We talk about Conversational AI a lot on our website and blog, after all this technology is at the core of what we do at The Bot Forge.
You may well have encountered some of the different terminology used. But what do developers and technologists really mean when they use these terms? Having a simple understanding of some of the more frequently used terms can be useful when thinking and talking about your chatbot or voice assistant strategy. This conversational AI terminology cheatsheet aims to help you understand; no technical knowledge required!

  1. Algorithm

    An algorithm is a formula for completing a task. Wikipedia states that an algorithm “is a step-by-step procedure for calculations. Algorithms are used for calculating, automated processing and data processing and provide the foundations for artificial intelligence technology.

  2. Artificial Neural Network

    Artificial Neural Networks or ANN are artificial replicas of the biological networks in our brain and are a type of machine learning.  Although nowhere near as powerful as our own brains they can still perform complex tasks such as playing chess, for example AlphaZero, the game playing AI created by Google.

  3. Artificial Intelligence

    AI research and development aims to enable computers to make decisions and solve problems. The term is actually a field of computer science and is used to describe any part of AI technology of which there are 3 main distinctions (1)

  4. Big Data

    Big data describes the large volume of data – both structured and unstructured – that floods through a business and its processes on a day-to-day basis. In the context of AI big data is the fuel which is processed to provide inputs for surfacing patterns and making predictions.

  5. Chatbots

    I think we have mentioned these once or twice! A chatbot is a conversational interface powered by AI and specifically NLP. They can be text-based, living in apps such as Facebook Messenger or their interface can use voice-enabled technology such as Amazon Alexa.

  6. Cognitive

    Cognitive computing mimics the way the human brain thinks by making use of machine learning techniques. As researchers move closer towards transformative artificial intelligence, cognitive will become increasingly relevant.

  7. Conversational Design/Conversational Designer

    Whilst not a technical term its a relatively new role which has grown to being a vital one with the rise in the popularity of conversational experiences. It’s important to understand what this new breed of skilled professional brings to a chatbot project and why they are so important. Conversation design is the art of teaching computers to communicate the way humans do. It’s an area that requires knowledge of UX design, psychology, audio design, linguistics, and copywriting. All of that put together helps chatbot designers create natural conversations that guarantee a good user experience.

  8. Deep Learning

    Also known as a deep neural network, deep learning uses algorithms to understand data and datasets. Deep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep Learning techniques have become popular in solving traditional Natural Language Processing problems like Sentiment Analysis.

  9. Entity and Entity Extraction

    Entities are also sometimes referred to as slots. An entity is used for extracting parameter values from natural language inputs. Any important data you want to get from a user’s request will have a corresponding entity.  Entity extraction techniques are used to identify and extract different entities. This can be regex extraction, Dictionary extraction, complex pattern-based extraction or statistical extraction. For example, if asked for your favourite colour you would reply “my favourite colour is red”. Dictionary extraction would be used to extract the red for the colour entity. What that means in the real world is types of product, locations, model numbers, parts numbers, courses etc: basically anything related to your business which needs to be understood and extracted from the conversation.

  10. Intelligent Personal Assistants

    This term is often used to describe voice-activated assistants which perform tasks for us such as Amazon Alexa, Google Assistant, Siri etc instead of text-based chatbots.

  11. Intent

    An intent represents a mapping between what a user says and what action should be taken by your chatbot. A good rule of thumb is to have An intent is often named after the action completed for example FindProductInformation, ReportHardWareProblem  or FundraisingEnquiry.

  12. Machine Learning

    Machine Learning or ML for short is probably used by you every day in Google search for example or Facebooks image recognition. ML allows software packages to be more accurate in predicting an outcome without being explicitly programmed. Machine learning algorithms take input data and use statistical analysis to predict an outcome within a given range. Machine learning methods include pattern recognition, natural language processing and data mining.

  13. Natural Language Processing

    Natural language processing (NLP) is broadly defined as the automatic manipulation of natural language, like speech and text, by software. NLP is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language. NLP draws from many disciplines, including computer science and computational linguistics to fill the gap between human communication and computer understanding.

  14. Natural Language Understanding

    A subfield of NLP called natural language understanding (NLU) has begun to rise in popularity because of its potential in cognitive and AI applications. NLU goes beyond the structural understanding of language to interpret intent, resolve context and word ambiguity, and even generate well-formed human language on its own.

    NLU algorithms tackle the extremely complex problem of semantic interpretation. That is understanding the intended meaning of spoken or written language. Advances in NLU are enabling us create more natural conversations.

  15. Sentiment Analysis.

    Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral. More advanced analysis would look at emotional states such as “angry”, “sad”, and “happy”.

  16. Utterance

    An utterance is anything the user says via text or speech. For example, if a user types “what is my favourite colour”, the entire sentence is the utterance.

  17. Conversational IVR

    Conversational IVR is a software system which uses voice commands from customers. This allows them to interact with IVR systems over telephony channels.

    Whereas traditional IVR systems had speech recognition technology to handle simple voice commands such as “yes” or “no”.  Conversational IVR allows people to communicate their inquiries in more complete phrases via a natural language understanding. Callers can describe questions or concerns in their own words which is then matched to an intent by natural language understanding.

We hope you have found this Conversational AI Terminology Cheat-sheet helpful. If you want to talk about your chatbot project contact us at The Bot Forge

Comment if you think I’ve missed any terms out which should be on the cheat sheet

This example of a chatbot from Shimano which was launched in Facebook Messenger. Facebook users can find information about their products, events, technical documentation and a link through to a dealer locator. We particularly like the product recommendations functionality as it demonstrates how a smart recommendation can drive sales.

 

I spent a bit more time looking at the Shimano chatbot today. I posted about this all the way back in 2018. This particular chatbot looks like it needs a bit of an overhaul as I didn’t seem to get any response about recommendations. To me it highlights the need to monitor and improve chatbot capabilities.

Screenshot of the Shimano chatbot

However the menu system menu is used to good effect enabling users to contact customer support directly.

I was disappointed that when typing help I got the dreaded “I’m sorry but I did not understand that” message. At The Bot Forge we feel this is a simple quick win with chatbot useability. If a chatbot trips up whilst handling a query then users will often type help to try and get back on track.