What is a Facebook Messenger chatbot

Chatbots are customized to get questions, give answers, and execute errands. They provide helpful advice 24/7 and provide advanced customer support and marketing and sales tasks.

Chatbots have been around for quite a long time, and can be deployed onto website pages, in applications, via online media—and so on. They can also be deployed into chat applications

A Facebook Messenger bot is a chatbot that lives in Facebook Messenger, which means it banters with a portion of the 1.3 billion individuals who use Facebook Messenger consistently.

If you are on Facebook, you most likely as of now have a Facebook Messenger technique. A Facebook Messenger chatbot will allow you to scale your strategy.

As of 2018, there were more than 300,000 Messenger bots and this number has been increasing since then.

The benefits of using a Facebook Messenger chatbot

Facebook Messenger chatbots are great for:

  • Reaching your audience
  • Save time and money with customer support costs
  • Identifying leads
  • Handling transactions
  • Engaging with your customers

Each chatbot is as unique as the business it serves.

They can help with common customer service questions, like delivery tracking, appointment booking or product support questions.

They can also drive product discovery and sales assistance by asking qualifying questions to ensure the customer buys the best product for them.

A chatbot can be an effective tool to reach your customers and will often get better results than emails when engaging with your customer.

We are often asked this by clients looking to start their first chatbot project. Like most software projects the price really depends on the scale and complexity of the project. This will govern the effort involved to build the bot and define whether it needs to be a custom chatbot or off the shelf solution.

So, let’s take a look at the key drivers impacting the price for custom chatbot development.

Channel

The first one is the channel in which the bot should function. By this, I mean where the bot will be used. It could be as a website widget implemented as a popup interface or webpage (You can learn more about webpage chatbots here) or deployed into existing messaging platforms. Facebook Messenger, Slack, Telegram, Viber, Google Assitant are just a few examples with some providing more complex UI elements which can be utilised in your bot.

There are a number of really good bot building platforms for creating UI chatbot interfaces such as Botstar, Chatfuel and Manychat; these offer some free templates and the ability to create chatbots which can be deployed to websites and Facebook Messenger. These Bot building platforms offer some good features: Visual Flow Editors, APIs & Webhook Integrations, Templates, Broadcasting etc. In our experience, we have found that even with free templates there are some costs due to setup and minor customisation. So our minimum price is around £600 with some monthly costs for hosting and chatbot management and training.

Natural Language Ability

If a chatbot is required to support more complex natural language processing features and not just UI elements such as buttons then this will mean that additional effort is needed to train the bot and design and implement a more complex conversational flow. These sort of bots start at around £1500. We utilise Dialogflow Natural Language Processing to offer these types of solutions.

The complexity, scope and volume of the required conversational ability effects cost. This relates to specifics such as:
Number of branches in the conversation tree.
Quantity of questions that have to be handled by the chatbot which can often be in the 1000s.
The complexity of conversational ability ie. support for complex user enquires.
So chatbots which combine richer elements with complex conversational ability can be in the region of £1500 – £3000

Integration

The other area which will impact cost is dependent: what the chatbot will need to do carry out its role? Will the chatbot need to integrate with current systems to provide its responses? Will it need to hand over to live agents? Connect with CRM and ticketing solutions? Some chatbots may need to carry out complex interactions to provide answers to customer queries. Bots can even call systems utilising Artificial intelligence to provide relevant information based on historical chat data, for example using, https://www.tensorflow.org.  With so many possibilities for bot features It’s hard to estimate the price here, but these types of chatbots cost from £4000.  For each integration, we would suggest a cost of £1000-2000 it really depends on the amount of development effort required for each one.

Languages and Features

Chatbots are capable of supporting different languages, as long as these are supported by the NLP engine it’s possible to add different language permutations fairly easily. However, each language will need its own testing so costs can be in the region of £500-1000 for each language.

Finally, depending on which channel the bot will work in there is also scope to provide other functionality such as voice capability for web chatbots or enhanced chatbot interface features. Again costs depend on the amount of complexity and effort involved in building each feature. As an example adding voice interaction to a Web chatbot would be £500.

Flexibility

As you can see, the cost of a chatbot project can vary dependent on the features required. However, the cost of a capable chatbot does not have to be prohibitive and it’s often a good idea to start small and add features as business needs require them.

At The Bot Forge, whatever the cost we propose for your chatbot project our aim is to create value for your business and hopefully form a long-lasting relationship.

6 Reasons you need a chatbot to support your sports event Taking a 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 […]

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.

Fred Whitton sports event chatbot interface

 

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.

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.