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If you are looking to streamline certain operations of your business, implementing a chatbot is a great way to go about it. After all, you can use technologies such as artificial intelligence (AI) and natural language processing (NLP) so that it can follow different types of conversations with users and provide relevant responses where necessary.

Chatbots are no longer a gimmicky tool available on the internet, as they have gained popularity and sophistication many users are incorporating them into their digital strategy. For example, a large number of businesses now use bots as part of their customer service. As these chatbots never go offline, they are always available to assist users, at any given time of day.

It is a lot cheaper for a business to implement a bot as part of its customer service than hire employees. If you employ an individual, you have to train the person and provide a salary and vacation time. One example is one of our clients https://amicable.io who replaced call centre resource with a chatbot to book client meetings.

Chatbots have a lot of advantages, which explains why businesses want to make the most of them. However, while creating these bots, it is natural to make errors, which hampers the user experience. As this might be the first or nth time you are developing a chatbot, you want to make sure it functions as expected. Here are six common mistakes to avoid along with how you can overcome them:

Assuming every user wants to talk

You tend to believe that everyone who visits your page or installs the chatbot on Slack, or other popular messaging platforms wish to start talking to it immediately. However, most of the people on the internet don’t want to communicate with the bot, unless it is necessary.

One reason why chatbots are great marketing tools is that they can engage with prospects by answering important questions. As a result, it brings down the sales friction, making it simpler for the user to invest in what you have to offer.

If your bot starts to message the individual as soon as he/she opens it, there is a high chance the person will find it annoying. A better practice would be to wait for the user to respond or you can leave instructions in the description on how to start conversing with the chatbot. Our sports events Facebook Messenger chatbot Carly utilises this kind of functionality enabling users to set push notifications for their any new sports events based on their own criteria.

Failing to track its performance

Since the chatbot makes use of the latest technological advancements in the industry, you might assume that you shouldn’t keep an eye on its performance. After all, you spent a considerable portion of your time training it, so that it can have a continuous conversation with your customers.

However, you will never know the effectiveness of your bot, if you don’t track the key performance indicators (KPI). These metrics provide a deeper insight into how you can continue to improve your chatbot. For example, you can see where most of the users tend to leave the conversation. With this data, you can think of different ways to keep them engaged so that they continue to talk to your bot. We feel that the history and training tools provided by Dialogflow enable us to track chatbot performance effectively.

Forgetting to list in directories

Once the chatbot is up and running on various messaging platforms or your website, you think you completed your job. All your visitors have to do is start talking to the bot, and it will help them in their tasks.

However, not everyone will know about the existence of your chatbot. Several messaging platforms may not have powerful search, which makes it harder to discover your bot. The best practice is to find third-party websites and lists your chatbot in it. As a result, if people look for your bot on Google or other search engines, the chances of it popping up in the first page of results goes up significantly. The best place to market your own new bot is on your website, why not write a blog post about your chatbot journey, you can guarantee other companies will be interested in your journey.

Impersonal conversations

The reason why people don’t like talking to bots is that the conversation tends to be boring and bland. As a result, they prefer to converse with human beings, as the experience is better in every way.

Think about it, would you like talking to a chatbot which sounds like it is speaking in a monotone? Rather than putting your bot in the same position, you should think of different ways to spice up the conversation. For example, you can ask the user what the chatbot should call the individual while talking to one another.

One thing is key here and we have seen this in our experience: to gain better customer satisfaction it’s better to explain to your users that your bot is a chatbot and not try and masquerade as a human. If users are aware they are talking to a chatbot from the off it will gain confidence and improve the customer experience as the user becomes more forgiving.

Not paying attention to its tone

Since the entire conversation between the chatbot and its users is going to take place via text, you need to pay close attention to its tone. Using the right type of communication will determine whether your bot performs well among its intended target audience.

While this tends to be challenging, there are several ways you can overcome this obstacle. For example, you can ask a small number of people from your target audience, what tone they would find appropriate. At the same time, you can also have a beta group, which allows you to experiment and see which one works well. Matching tone to the industry and subject matter is important to build a satisfying experience for your chatbot users.

Help and Live Agents

Since the purpose of the chatbot is to reduce the workload of your employees, you tend to assume that you don’t need a live agent. The problem with testing is that it may not take into account all the variables present in real-world scenarios. As a result, when you deploy your chatbot, it might not know how to handle a specific question.

Due to this reason, it can go on an endless loop, and the only way out of the conversation is to quit or restart the chatbot. An excellent way to overcome this problem is to allow your chatbot to ask a live agent to join the conversation during this situation. Once the employee helps out the user, he/she can provide information to the developers on how to improve the communication skills of the bot.

It’s also important to provide easy help for users to access during the bot conversation. At The Bot Forge we always implement a help feature for our chatbots so users know what they can do and how they get back on track our Facebook Messenger chatbot for the Fred Whitton Challenge is a perfect example.

Chatbots are becoming a great tool for businesses. You can use them to make life easier for your clients, by assisting them in various functions. By knowing what the common mistakes are, you can avoid them entirely and design the best bots in the industry

The post Developing a Chatbot? 6 Common Mistakes to Avoid appeared first on The Bot Forge.

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Dialogflow is Google’s human-computer interaction developer which is based on natural language conversations. At The Bot Forge, Dialogflow is our platform of choice for chatbot construction.

There’s three main reasons for why we’re amongst companies such as Domino’s and Ticketmaster who make Dialogflow their chatbot platform of choice.

  1. Flexible coding: Thanks to Dialogflow’s in-line code editor, the time taken to complete code-related tasks is quicker than with other platforms. The prime benefit here is that we’re then able to spend more time perfecting the conversational experience.
  2. Scalability: Whether you start with 1,000 or 100,000 users, the platform can scale to your needs. As Dialogflow is hosted on the Google Cloud Platform, this allows the potential to support a user base of hundreds of millions, if required.
  3. Inbuilt machine learning: Arguably the biggest benefit of the platform in comparison to others is the availability of machine learning and natural language processing technologies. The access to these features allow us to create a richer and more natural conversational experience for your users. Dialogflow makes this possible by allowing us to extract data from a given conversation, in order to train our agents to understand user intents. Plus, as the technologies are already built into the platform, we’re able to construct your application much faster.

To ensure that we’re using the right platform for our clients’ needs, we continuously refresh our knowledge of other bot construction tools, such as The Microsoft Bot Framework. A benefit of using this platform from a developer’s perspective is the availability of templates to choose from, which allow for a more time efficient development. The IBM Watson Assistant is another platform that a developer may favour, as the testing the bot is simpler than it is on other competing platforms. If a priority is to feature your bot over a wide range of locations, Recast.AI may be a good option for its availability on 14 different platforms.

But, these platforms aren’t without their weaknesses. Unlike Dialogflow, Microsoft Bot Framework is lacking in the tools which help to create the “brains” of the bot, which is important for the sophistication that users are beginning to expect. Also, a downside of IBM Watson Assistant is the unintuitive relationship between intents (representation of user’s meaning) and entities (expressions recognised in categories). If you’re interested in how Dialogflow utilises intents and entities, we will be covering this in a future blog post.

Although we understand that there are features of other platforms which can make the development process more efficient, the inbuilt machine learning features of Dialogflow means we can deliver a bot that can produce a much richer conversational experience.

The post Why Dialogflow? appeared first on The Bot Forge.

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The Dialogflow team announced that they would be deprecating their V1 version of the Dialogflow api in Oct 2019

You can read about their official announcement here

The Bot Forge have been following the progress of the latest V2 api since its official launch in April this year, it’s no surprise that the Dialogflow team have made this announcement as they concentrate their efforts on the new API. However it does have some serious implications for existing chatbots utilising the v1 API.

Migration

You can see some more details about upgrading from V1 to V2 in the official guide here. We also aim to provide some more detailed information about carrying out an upgrade on this blog so watch out for that.

Anyone who already has built out their website chatbots using v1 API, then they should start planning for the migration sooner rather than later. Any new features should be added after the upgrade. The migration is potentially a non-trivial task, considering some chatbots have some fairly complex code driving their fulfilment. If you have a live bot in production our advice is to set up an upgrade chatbot as a copy of your existing bot project and then work through the upgrade there. You can guarantee that changing to V2 will mean that fulfilment and API calls may stop working. Once the upgrade is complete re-testing all bot functionality is strongly advised before setting live.

Chatbot Web Interfaces

We would recommend everyone who is creating custom website chatbots to do so using the v2 API. All our new chatbots are built using the v2API.

The big change for v2 is that it uses Google’s OAuth2 for its authentication, with v1 you could simply use the client access token when calling the v1 API. Implementing the features required to authenticate against the new v2 API means some significant extra development effort.

If you need assistance or advice with your own chatbot v2 upgrade please get in touch, we are Dialogflow experts and would be happy to help!

At the Bot Forge, we specialise in building chatbots so you feel free to contact us if you want to discuss further.

The post Dialogflow Announce v1 API will be deprecated in October 2019 appeared first on The Bot Forge.

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Chatbots For Business

The business landscape is evolving faster and faster, we look at using chatbots for business to help you remain competitive.

There is so much coverage of artificial intelligence technology and chatbots these days  There is no doubt that chatbots are big news for many different industries, from e-commerce and fashion to healthcare and banking.

Whilst many big brands have already jumped at the opportunity to leverage the technology for others it’s challenging to see where they can be a benefit to your company and whether the cost and effort involved is worthwhile. Some of you may remember many years ago when you were approached by someone selling a shiny website and then later on a new app? You probably asked yourself a similar set of questions..that’s nice and shiny but why do I want it? is it right for us? First things first let’s look at some of the basics.

The chatbot lowdown What is a chatbot?

Briefly put a chatbot is a service, powered by natural language processing rules and artificial intelligence (AI), that you interact with via a voice or text-based chat interface. AI technology is used to enable the service to respond to specific user interaction. For example, a user could ask a chatbot a question or give it an instruction and the bot could respond or perform an action as appropriate.

This chat service can take on any number of roles, providing answers, collecting customer information, suggesting products and making sales. They can live in any major chat product (Facebook Messenger, Skype, SMS, Slack, Telegram, Viber, Twitter, Website). They can also be deployed into voice-enabled assistants such as Amazon Echo or Google home. Chatbots can also be developed to include multiple language capability.

Where can a chatbot be used?

Chatbots have been deployed in many different guises as they are extremely flexible and able to take on whatever business need arises.

You could say the possibilities are endless, here are some examples:

Celebrity

www.m.me/katyperry
Katy Perry’s official Facebook Messenger bot.

Customer Service

Vodafone TOBi
Vodafone’s customer service chatbot is based on IBM’s Watson & provides a fully integrated webchat for customers.

Productivity

AceBot
https://slack.com/apps/A0GRU84TF-ace
AceBot a productivity tool with expense tracking & intelligent task management, deployed in Slack.

Sports and Events

www.m.me/fredwhittonchallenge
The Saddleback Fred Whitton Challenge sportive bot is a smart events assistant providing event info to participants.

E-Commerce

www.m.me/LEGO
The official Lego Facebook Messenger bot. Ready to help your next LEGO purchase.

Health

www.m.me/superizzyai
Izzy is a period tracking and pill reminder chatbot.

The benefits of using chatbots for your business Provide stellar customer service 24/7

For many businesses, the biggest challenge to serving your customers in several communication channels is responding quickly all of the time.

Constantly available

One of the great benefits of a chatbot is the constant availability. Customer expectations are high expecting a quick response to enquiries. With a chatbot, you can offer your customers a 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.

One example from my own personal experience was with a SAAS which had charged me incorrectly for an amount of money which caused my bank account to go overdrawn. I contacted the customer support chatbot via a web interface at 1 AM and the problem was rectified and money returned promptly the next day. I went from disgruntled to a satisfied customer in a 5-minute chatbot interaction, incidentally, I’m still a customer!

It’s also worth noting that chatbots can be enabled to understand multiple languages. NLP technology will understand queries in different languages and respond appropriately. So if you support a global customer base needing to support multiple language enquiries this does not have to be a problem.

System integration

With the correct integration development, a chatbot is able to answer complex enquiries by integrating with existing CRM, ERP, CMS, and other business-critical applications.
Connect your chatbot seamlessly with your entire business ecosystem.

Scalable

Chatbots are scalable and capable of handling multiple enquiries, ready to step up when enquiry demands are at their peak.

A well implemented and executed chatbot can give businesses 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 businesses in freeing up staff to deal with the more complex issues.

Although a chatbot cannot handle all customer queries, it can be used to deal with a large number of the routine business enquiries which most companies deal with on a day to day basis.

They improve customer satisfaction

To avoid frustration, a chatbot can be developed to use a “sentiment” function to pass users onto a real advisor if the bot can’t help or if they are not satisfied.
Other benefits can be seen in customer service gains. According to Jon Davies, head of digital at Vodafone, their customer service chatbot, TOBI provides “a far more engaging and personal” customer experience, as well as improving completion rates and reducing transaction times. These types of successes are highlighted in improved net promoter scores (NPS).

Overall chatbots for business can excel in supporting customer service teams in their communications with customers. Providing accessible information 24/7 saves businesses money and time. By 2022 chatbots are expected to save $8 billion7.

Drive sales, engagement, reach

These days customers are savvier and demand an intuitive and seamless customer experience. Businesses need to consider using technology to fit in with their communication habits.

Familiar messaging technology

Many users prefer social media and mobile platforms for communication and expect businesses to be online 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. As of April 2017 Facebook Messenger had 1.2 billion monthly active users worldwide

Use these channels to reach new and existing customers.

It’s also important to note that 2 out of 3 customers actually prefer to message a business to submit an enquiry rather than use other more traditional channels such as email or phone. Every day 1.4 billion people around the world send over 50 billion messages to communicate with each other. As messaging becomes even more central in people’s lives, demand for service in messaging has continued to rise.

The rise of voice assistants

Voice assistant technology and it’s adoption has gathered serious momentum over the past couple of years. User expectations are rising as they become educated in what it can do. As customers realise that its capabilities go beyond setting a timer, turning down the lights or playing some music; they will look to this channel to make purchases, contact customer support or use as a tool for business specific tasks.

The latest from Google  Popular voice assistants currently include Apple’s Siri, Amazon’s Alexa, Google Now, Google Assistant and Microsoft’s Cortana. The big players are investing heavily in perfecting voice interfaces, read the latest from http://www.thebotforge.io/google-assistant-news-from-io2018/ and http://www.thebotforge.io/google-assistant-demo-duplex-makes-phonecall-io-2018/

The reach of this sort of technology cannot be underestimated. You can read some of the stats and predictions for voice technology here.

Marketing clout

As an effective marketing tool chatbots can give your company an edge as they can enter into personalized and automated communication with your customers.

Using platforms such as Facebook messenger, substituting emails with push notifications can obtain much higher click-through rates. Used wisely opt-in targeted messages or push notifications have 90% read rates and a 40% click-through rate. Chatbots can be used to send users personalised tips, greetings and information, generating leads, harvesting reviews and forging stronger customer relationships.

Utilising 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.

Businesses are finding chatbots to be a great tool to engage with their market: “Our target customers are early adopters of social innovation so a chatbot is the perfect vehicle for us to communicate with them”, Sarah Gower, Adidas.

Sales

Chatbots are ideal to answer first customer questions. if the chatbot decides that it can not effectively serve the customer, it can pass those customers to human agents. High value, responsive leads will be called by live agents increasing sales effectiveness.

Chatbots can be used to answer customer’s questions and promote products. Engage with the right customer by analyzing their profile and historical data and user characteristics. A bot can provide a channel for purchasing easily and quickly if requested.

Conclusion

I’ve really only scratched the surface of chatbot and voice interface technology capabilities and what can be achieved and how it can help your business be more competitive. However, it’s important to consider them carefully.  It’s up to the business to decide if a chatbot is a right move for them, for some the business case may not be there or something to consider in the future. Building a chatbot because you think you should or because its the latest thing can only result in wasted time, money and effort.

I hope you find this post helpful in considering how using chatbots for business can help you to achieve a competitive edge.

If you already have a chatbot idea and want to look into this further have a look at our post planning the best chatbot

At the Bot Forge, we specialise in building chatbots so you feel free to contact us if you want to discuss further.

The post Why using chatbots for business can help you remain competitive appeared first on The Bot Forge.

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AI Terminology Cheatsheet

Artificial Intelligence is talked about everywhere these days. In the news, media and extensively in science. We mention it 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 strategy. This 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. Autonomous

    Autonomy is the ability to act independently so software which can complete tasks on its own is autonomous for example systems which manage self-driving cars.

  5. 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.

  6. 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.

  7. 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.

  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: 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.

  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 UserProvidedColor.

  12. Machine Learning

    Probably used by you every day in Google search for example or Facebooks image recognition. Machine learning 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) enables machines to understand human language. Machine learning is used to find patterns within large sets of language data sets in order to recognise natural language and aid machines in understanding sentiment so that they can respond correctly.

  14. Sentiment Analysis.

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

  15. 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.

We hope you have found this AI Terminology Cheatsheet 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 cheatsheet

The post The Non-Technical Guide to Popular AI Terminology appeared first on The Bot Forge.

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Chatbots 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.

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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).

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.

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.

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

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.

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.

These are just 6 reasons we’ve covered

It’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

The post 6 Reasons you need a chatbot to support your sports event appeared first on The Bot Forge.

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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 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.

Fred Whitton Chatbot FAQs - YouTube

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.

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.

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

The post Learn how AI powered sports software helped event organisers appeared first on The Bot Forge.

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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 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.

Fred Whitton Chatbot FAQs - YouTube

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.

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.

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

The post Learn how AI powered sports software helped event organisers appeared first on The Bot Forge.

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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 

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.

The post Read about our Chatbot in the inBusiness Science and Technology spotlight appeared first on The Bot Forge.

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