Conversational UI to create natural conversational experience

What is Conversational UI

So what is Conversational UI? Historically interfaces or UI has been made up of visual elements: buttons, dropdown lists, date pickers, carousels. Now we have the technology to provide conversational ones as well via voice or text-enabled interfaces such as Amazon Echo or Facebook Messenger. Some applications also leverage the best of both worlds, combining traditional UI elements with conversational capability: for example Facebook Messenger.

The most important advancement in Conversational UI has been Natural Language Processing (NLP). This is the field of computing that deals with deciphering the exact words that a user and parsing out of it their actual intent and in what context. You can read about some of the terminologies here. If the bot is the interface, NLP is the brain behind its conversational ability.

Natural Conversational Experiences

The Bot Forge creates natural conversational experiences for voice and text-based applications leveraging the latest AI technology.

Our team is made up of natural language processing (NLP) and Natural language understanding (NLU) experts, artificial intelligence specialists, conversational architects, project managers, and interaction designers. Focused on forging engaging voice and text-based Conversational UI powered by NLP.

Our conversational interfaces can be deployed on websites, mobile applications, messaging applications and voice-enabled devices.

We use the most advanced machine learning technology to power our solutions so that recognising user intent and context works reliably and seamlessly. Our goal is to create awesome conversational experiences.

How Much Does It Cost To Build A Chatbot In 2020?

Artificial Intelligence, Chatbots, Conversational UI, Facebook Messenger

We are often asked this question 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 in building a chatbot.

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, WhatsApp (read more about WhatsApp chatbots here), Microsoft Teams, Slack, Telegram, Viber are just a few examples with some providing more complex UI elements which can be utilised in your bot. Other obvious channels to deploy a chatbot are voice; Google Assistant, Alexa or even IVR systems can often use the same conversational engine as your text-based chatbots.

For our custom chatbot integrations, we normally provide one channel with the project and then charge per extra channels as required. We’ve found that our clients will often want a web-based chatbot first and role out the chatbot onto different channels. It really does depend on the type of project. Extra channel costs can be in the region of £1000-2500.

There are a number of really good chatbot building platforms for creating simple 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 specific channels, for example, Facebook Messenger (our Carly chatbot is a great example of a Chatfuel bot). These Bot building platforms offer some good features: Visual Flow Editors, APIs & Webhook Integrations, Templates, Broadcasting etc. However, in our experience, we have found that even with free templates there is always some costs due to setup and minor customisation to attain the maximum chatbot behaviour. Our minimum price is around £1500 with some monthly costs for hosting and chatbot management and training.

Features

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 capability to a Web chatbot would be £1000. Human-agent handover or WhatsApp integration is also a popular feature.

Natural Language Ability

If a chatbot is required to support more complex natural language processing(NLP- you can read more about some of the tech terms here) 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 £2500. We utilise the best of breed cloud NLP solutions for these types of projects. In particular, we use Google Dialogflow as we are Google Tech partners and experts in Dialogflow.

Conversation skills

The complexity, scope and volume of the required conversational ability effects cost. This relates to specifics such as:

The 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 numbers of training phrases needed; this can improve the accuracy of the chatbot, (you can read more about training data here)
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 £2500 – £5000

Languages

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 £1500-3500 for each language depending on the size and complexity of the conversational ability.

Integration

Connect to existing systems, APIs, RPA, and knowledge bases

The other area which will impact cost is dependent on the planned role of the chatbot: 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. Chatbots can leverage other AI systems to provide relevant information to govern conversational flow. For example, sentiment analysis.

With so many possibilities for chat bot features It’s hard to estimate the price here, but as a rule, these types of chatbots cost from £4000. For each integration, we would suggest a cost of £1000-2500 it really depends on the amount of development effort required for each one.

Deployment

Security

Often security demands for a chatbot project need specific features, for example, Hippa compliance. In these cases SSO, RBAC, and on-prem or private cloud deployment can be used to ensure compliance with company security policies. These can have an impact on overall project costs and again, costs are based on the demands of a specific project.

Maintenance

We offer our chatbot solutions based on a SAAS model. Costs incurred tend to be based on a yearly subscription and again depend a lot on the scale and complexity of the chatbot. These monthly costs will cover some of the following:

Daily supervised learning and improvements.
Monitoring conversations and confirming qualified intents as well as checking for unmatched intents and fixing them as needed.
Post-development support.
Third-party and integration maintenance. Making sure your bot is performing well and healthy!
NLP costs(if applicable).
Hosting and data storage.
Chatbot reporting interface.

As a rule, maintenance subscription costs tend to be in the region of 10-15% of initial implementation costs per month.

Flexibility

As you can see, the cost of a chatbot project can vary widely depending on the features required. Each chatbot project is different.

It’s worth keeping in mind that 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.

The Bot Forge are always available to discuss further improvements and functionality to add to your chatbot or just to talk to us about your next great idea.

February 10, 2020/0 Comments/by ajwthompson

Training a chatbot

Chatbots, Conversational UI

Training data for chatbots.

I’m going to look at the challenges in creating a chatbot which can answer questions about its specific domain effectively. In particular, I’m going to look at the challenges and possible solutions in creating a chatbot with a reasonable conversational ability at their initial implementation. Every chatbot project is different but often clients come to us with a large knowledge base which they want a chatbot to support from its release but with very little training data.

We are going to concentrate on a Dialogflow project to look at some examples however the challenges and solution are similar for all the most well know NLP engines, Watson, Rasa, Luis etc.

The Challenge

One of the key problems with modern chatbot generation is that they need large amounts of chatbot training data.
If you want your chatbot to understand a specific intention, you need to provide it with a large number of phrases that convey that intention. In a Dialogflow agent, these training phrases are called utterances and Dialogflow stipulate at least 10 training phrases to each intent.

Depending on the field of application for the chatbot, thousands of inquiries in a specific subject area can be required to make it ready for use with each one of these lines of enquiry needing multiple training phrases.

The training process of an ai powered chatbot means that chatbots learn from each new inquiry. The more requests a chatbot has processed, the better trained it is. The NLU(Natural Language Understanding) is continually improved, and the bot’s detection patterns are refined. Unfortunately, a large number of additional queries are necessary to optimize the bot, working towards the goal of reaching a recognition rate approaching 90-100% often means a long bedding in process of several months.

Data Scarcity

One of the main issues in today’s chatbots generation is that large amounts of training information are required to match the challenges described previously. You have to give it a large number of phrases that convey your purpose if you want your chatbot to understand a specific intention.

To date, these large training corpus had to be manually generated. This can be a time-consuming job with an associated increase in the cost of the project. One of the main issues we have faced is that often clients want to see quick results in a chatbot implementation. These types of chatbot projects are often use cases which are providing information regarding a wide-ranging domain and may not necessarily have a lot of chat transcripts or emails to work with to create the initial training model. In these cases there is often not enough training data and so it takes time to get decent and accurate match rates.

The Solution

THE BOT FORGE PROVIDES
CHATBOT TRAINING DATA
CREATION SERVICES

The Bot Forge offers an artificial training data service to automate training phrase creation for your specific domain or chatbot use-case. Our process will automatically generate intent variation datasets that cover all of the different ways that users from different demographic groups might call the same intent which can be used as the base training for your chatbot.

Multi NLP platform support
Multi-language support

Our training data is not restricted solely to Dialogflow agents, the output data can be formatted for the following agent types:

rasa: Rasa JSON format
luis: LUIS JSON format
witai: Wit.ai JSON format
watson: Watson JSON format
lex: Lex JSON format
dialogflow: Dialogflow JSON format

We provide training datasets in 100+ languages

We offer our synthetic training data creation services to our chatbot clients. However, if you already have your own chatbot project and just want to boost its conversational ability we can provide synthetic training data to meet your needs.

Testing the Solution

We wanted to test the effectiveness of using our synthetic training data in a Dialogflow chatbot agent by varying the number of utterances per intent using our own synthetic training data.

Dialogflow test agents

We carried out three different tests (A B and C) with 3 separate Dialogflow agents. Each agent had identical agent settings. The agents had 3 identical intents to provide information about the topic of angel investors:

what_is_an_angel_investor
what_percentage_do_angel_investors_want
do_angel_investors_seek_control

In the first test (A) the chatbot was trained with 2 hand-tagged training phrases (utterances) per intent. Test (B) had 10 training phrases from our own synthetic training data per intent and test (C) had between 25 and 60 training phrases per intent.

The Test

We tested each agent with 12 separate questions similar to but distinct from the ones in the training sets.

We didn’t carry out any training during testing once the chatbots were created.

We recorded the % of queries matched to the correct intent, the incorrect intent or no match and also the intent detection confidence 0.0 (completely uncertain) to 1.0 (completely certain) from the agent response.

Overall test results

View the results here


	% correct match rate	% incorrect match	%no match	Average Intent Detection Confidence
Test A (2x utterances)	50%	42%	8%	0.6437837225
Test B (10x utterances)	91%	9%	0%	0.7590197883
Test C (25-60x utterances)	100%	0%	0%	0.856748325

Test A provided a 50% match rate. We observed a significant improvement in test B with the introduction of some of our synthetic training data to the agent. We were able to improve the match rate from 41% to 91% whilst TestC with 25-60 training phrases enabled a match rate of 100%. The average intent detection confidence also grew

In summary, chatbots need a decent amount of training data to provide accurate results. If there is not enough training data then a chatbots accuracy is affected and it can take some time to train it whilst being used to reach acceptable performance levels. At the same time, it can be costly and time-consuming to create training data for a chatbot needing to handle large numbers of intents.

Our synthetic training data creation service allows us to create big training sets with no effort thus reducing initial costs in chatbot creation and improving the usability of a chatbot from the initial release stages. If you only have a limited number of training phrases per intent and have large numbers of intents, our service is able to generate the rest of variants needed to go from really poor results to a chatbot with greater levels of accuracy in providing responses. We have carried out these tests with Dialogflow, but our conclusions are relevant for ML-based bot platforms in general. We can conclude that our Artificial Training Data service is able to drastically improve the results of chatbot platforms that are highly dependent on training data

Chatbot Training Never Ends!

I’ve looked at the benefits of using our training data at the early stages of a chatbot project. However, it’s important to note that the key to success, in the long run, is to constantly monitor your chatbot and continue training to get smarter. Either by doing constant training with human effort or by scheduling regular training cycles, incorporating new utterances and conversations from real users.

If you want to know more about our chatbot training data creation services get in touch

Appendix

View the test results here

January 31, 2020/0 Comments/by ajwthompson

Chatbot Technology Landscape – AI Platforms

Artificial Intelligence, Chatbots, Conversational UI, Technology

We build a lot of different types of chatbots at The Bot Forge and deliver these to a variety of platforms such as Web, Facebook Messenger, Slack or WhatsApp. To create our chat bots we often use different AI platforms which offer more suitable features for a specific project. All the major cloud and open-source providers have adopted similar sets of features for their conversational AI platforms and provide good NLU (Natural Language Understanding). There are also some strong options for open source privately hosted systems.

Conversational AI Platform Features

We wanted to spend some time looking at some of the more popular AI platforms in a bit more depth in this series. To help look at each one we have focused on the following specific features:

API and UI

A conversational AI platform should provide User Interface(UI) tools to plan conversational flow and help train and update the system

Context

As well as intent and entities, a context object allows the system to keep track of context discussed within the conversation, other information about the user’s situation, and where the conversation is up to. This is often the NLP feature which is vital in creating a complex conversation beyond a simple FAQ bot.

Conversation flow

Looking at the current position of a conversation, the context and the user’s last utterance with intents and entities all come together as rules to manage the conversational flow. This can be challenging to create and manage so a platforms’ tools in the form of a flow engine, in code and complimented by a visual tool can provide advantages depending on the chatbot project itself. Other features such as slot-filling (ensuring
that all the entities for an intent are present, and prompting the user for any that are missing) can be important.

Whilst most platforms fall into this category some systems use machine learning to learn from test conversational data and then create a probabilistic model to control flow. These systems rely on large datasets.

Pre-built channel integrations

Having a conversational platform that supports your target channel out-of-the-box can substantially speed up delivery of a chatbot solution and your flexibility in using the same conversational engine for a different integration. This is one of the reasons we really like Dialogflow’s tooling.

Chatbot Content Types

Whist the focus of a conversational AI platform is understanding pure text, messaging systems and web interfaces often involve other content, such as buttons, images, emojis, URLs and voice input/output. The ability of a platform to support these features is important to create a rich user experience and help to manage the conversational flow.

Integrations

Bot responses can be enhanced by integrating information from the user with information from internal or external web services. We use this type of ability a lot in creating our chatbots and in our opinion feel its one of the most powerful features of a chatbot solution. With this in mind, the ability to configure calls to external services from within a conversation and use responses to manage conversational flow is important in building chatbot conversations.

Pre Trained Intents and Entities

Instead of creating entity types such as dates, places or currencies for each project some systems provide these pre-trained to deal with complex variations. In the same way, common user intents and utterances such as small-talk is offered pre-trained from some platforms.

Analytics and Logs

The key to creating a successful chatbot is that they need to be constantly trained and monitored. To aid in continuously improving the system once initially launched, the
conversational tools should provide a dashboard of the user conversations; showing stats for responses, user interactions and other metrics. Export of these logs is also useful to import into other systems. Other important AI features enable easily training missed intents, catching bad sentiments and monitoring flow.

Techstack

It can be important to take into account what libraries are provided by an AI platform and in what supported languages. In the end, this may favour your choice of solution if it fits with your current codebase or teams skillset. However, as a full-stack javascript software house, we find Node.JS to be our server stack of choice when building our bots and most AI platforms cater for this.

Costs

These are the costs for the cloud hosting and cloud NLU solutions. An important aspect to consider particularly for large scale enterprise chatbots handling large volumes of traffic where NLU costs can reach £1000s a month.

Many providers offer a free tier for their AI platform solutions. A paid for tier will then normally offer enhanced versions of the service with enterprise focused features and support for greater volume and performance. Costs tend to be charged in one of 3 ways, per API call, per conversation or daily active user and also per active monthly user (normally subscriptions are in tiers). We try and look at costs as publicly published for the paid-for plans suitable for enterprise use in a shared public cloud environment.

The Platforms

Keeping all these feature sets in mind we hope to look at the following AI platforms over the coming posts.

Botkit
Chatfuel
Amazon Lex
Microsoft Luis
Google Dialogflow
Rasa
IBM Watson

Please get in touch if you feel we should look at a platform which we have missed!

Our first AI platform blog post will be coming soon!

November 5, 2019/0 Comments/by ajwthompson

How Much Does It Cost To Build A Chatbot In 2019?

Artificial Intelligence, Chatbots, Conversational UI, Facebook Messenger

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

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

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.

June 17, 2019/0 Comments/by ajwthompson

Developing a Chatbot? 6 Common Mistakes to Avoid

Artificial Intelligence, Chatbots, Conversational UI, Customer Support, Event Assistant, Facebook Messenger, Retail, Virtual Assistants

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

May 2, 2019/0 Comments/by ajwthompson

Dialogflow Announce v1 API will be deprecated in October 2019

Artificial Intelligence, Chatbots, Conversational UI, Dialogflow

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.

October 30, 2018/0 Comments/by ajwthompson

Why using chatbots for business can help you remain competitive

Artificial Intelligence, Chatbots, Conversational UI

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.

June 28, 2018/0 Comments/by ajwthompson

Planning the best chatbot

Artificial Intelligence, Chatbots, Conversational UI

Planning the best chatbot: 10 questions to answer

Congratulations you’ve had that lightbulb moment and you have an idea to create the best chatbot, or maybe you’ve heard so much about chatbots lately you feel you should explore the idea of using one for your company. If you want to read more about how a chatbot can help your company read our Why using chatbots for business can help you remain competitive blog post

Whatever the reason now its time to start looking at your idea in more detail to plan the best chatbot..but wait that can be hard. Don’t worry, we can help!

Chatbots have progressed rapidly over the past couple of years with advancements in Natural Language Processing (NLP) utilised used across voice and text driven interfaces. There has never been a better time to start a conversational UI project. However its still vitally important to plan your project carefully.

At The Bot Forge, we like to ask our clients the following questions to ensure we have a clear understanding of what they want to achieve with their chatbot project.

So whether you are looking at creating your own bot, or commisioning a team of chatbot experts like ourselves 😉 then it’s important to ask yourself the following 10 questions before you start building the best chatbot.

1. What is the purpose of your chatbot?

Why do you want to create a chatbot? What do you want the chatbot to do for your business and how will it achieve your business goals?

Right from the beginning of the project, it? s important for yourself and team to have a clear understanding about what your chatbot will do

2. What are the key goals of your chatbot?

What are the main aims of your chatbot? It could be to drive sales, provide 24/7 customer support or engage with new and existing customers by gathering customer feedback and delivering new product information.

3. How will you measure your chatbot’s success

How will you determine the success of your chatbot? What will your Key Performance Indicators (KPI) be?

For example, you could look at click-through rates, the numbers of enquiries handled correctly or feedback statistics gathered.

4. Who is going to use your chatbot?

Have a clear idea about who is going to use your chatbot, what will be the user demographic? This may influence your chatbot’s persona.

5. Where will your chatbot be deployed?

Your audience should drive your chatbot platform choice if possible. If you can collect information on which messenger platforms your audience use then this should assist your decision. Now is also a good time to consider voice platforms such as Alexa or Google Home.
With over 1 billion active users Facebook Messenger is our favourite messaging platform.

6. What will your chatbot do?

Here you can really start to consider what sort of functionality the chatbot needs to provide and most importantly the conversations it will be able to support.
A good way to capture chatbot requirements is by looking at them as user stories. The story is in the same format: As a , I want , so that: for example:
– I?m a participant, I want to check what time I can start my event, so that I can be ready to leave in good time.
– As a business, I want to collect customer reviews, so that I can improve their experience.
– As a customer, I want to access my account details quickly and receive an account update through my personal assistant.

7. Will the chatbot have a character?

Will the chatbot have its own persona, will it have a character?
Is the chatbot going to just be a polite assistant or does it need a character to carry through your brand?

8. How will the chatbot create value?

Think about the overall chatbot experience for users. How will the chatbot ensure that users come back?
For example by providing a simple and well executed personal assistant then customers are going to use this as their first port of call to find information and/or contact your company.

9. How will people find the chatbot?

How are you going to drive people to find and use your chatbot?
Links on your website and also advertising on Facebook can be great places to start as well as content on your Facebook page.

10. How will you look after your chatbot?

How will you monitor the chatbots performance after its launch? In comparison to other projects, it’s important to note that once the chatbot is launched this is just the start of your journey. Essentially you are at the start of the optimization phase. You will need to provide resources to get the most out of your chatbot after it’s launch.
You will need to monitor user interactions, reactions, unanswered requests: so you can train your chatbot and improve overall user experience, training your chatbot is key!

Conclusion

After working through these 10 questions you should be well on your way to understanding your chatbot concept.

With all our new clients at The Bot Forge chatbot agency, we ask them to fill out our chatbot checklist, feel free to download and work through with other members of your team.

We hope you find this post helpful in getting to grips with your chatbot project, feel free to share if you find the 10 questions useful.

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

June 15, 2018/0 Comments/by ajwthompson

6 Reasons you need a chatbot to support your sports event

Artificial Intelligence, Chatbots, Conversational UI, Event Assistant, Facebook Messenger

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.

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.

Conclusion

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.

June 8, 2018/0 Comments/by ajwthompson

Google Assistant news from io2018

Artificial Intelligence, Conversational UI, Google Assistant, Voice Assistant

ONSTAGE AT I/O 2018

In our last blog post, we looked at the totally mind-blowing demo of the new Google Assistant Duplex functionality. But there were some other exciting new features mentioned which we thought we should cover.

Google Assistant Features

Continued Conversation means you can keep talking without having to say “Hey Google”

If you currently use Google Assistant, you know that it’s annoying having to say “Hey Google” before every single command which can get annoying. Most conversations will incorporate follow-up questions if you didn’t get the answer you wanted or its natural to make another command.

With the new continued conversation feature which is going to be launched soon, you’ll be able to speak to the assistant and it will keep listening for a brief amount of time after the first command to make sure you are not following up with further commands. This is important as it will help make conversations feel more natural. Google says that Assistant will be able to understand when you’re taking to it or to someone else and will respond accordingly.

This feature is similar to the Alexa ‘follow up mode’ which became available a few months ago.

Custom Shopping Orders and Maps and Routines

Google have also improved the assistants shopping capabilities partnering up with Pizza Hut and Starbucks. Users can now order their favourite pizza or their usual coffee for delivery.

The Google Smart Display platform introduced earlier this year has also received Google Maps integration.

The custom routines feature which was launched earlier this year has also been extended. The routines feature enables you to do multiple things with one command. The new feature means you can now create your own custom routine, for example, you can create your own film night routine which turns down the lights, starts the film and notifies the rest of the house the film is starting. The ability to schedule routines is also coming soon.

More Google Assistant Voices

Published on July 24th, 2014 | by AlexandreG

If you are not into the current Google Assistant default voice, then you will soon have 6 to choose from, with the R&B singer John Legend featuring soon.

May 12, 2018/0 Comments/by ajwthompson

What is Conversational UI

Natural Conversational Experiences

The Bot Forge creates natural conversational experiences for voice and text-based applications leveraging the latest AI technology.

© 2020 The Bot Forge Ltd.

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