Salesforce Chatbots – New Frontier of Innovation
We’ve entered an era of chatbots. Interaction as a platform is here thanks to some major moves by Facebook, Microsoft, Telegram, and Salesforce, etc. Yeah yeah, we get it already. This is old news, anything new, you say.
Well, the brand new news is about how these bots are being received. The early response by the users has been lukewarm at best. They undoubtedly caught peoples’ attention, however, after some time, numerous users were not too excited by the unintelligent conversations they were having. It is where Natural Language Processing (NLP) comes to the rescue.
A quick dive into learning different aspects of chatbots
Determine availability of your bot
Working hours and channels
- Should your Bot be available for 24/7?
If you’re faced with a bulky load of calls and messages in your org that can be dealt with by bots then this technique makes sense. Some companies can improve their administration levels by serving customers on these broadly deployed platforms. But typically, the harder issue — is serving the customers right and connecting them with agents directly when required.
There are two significant factors you should consider to determine the availability of your Bot.
(i) Display chatbots based on team availability
Depending on team size – not everyone needs chat flows live on their site constantly. It should have an option, that can give you the alternative choice to make chat flows that respect your team’s availability schedule. If people want their user to only interact with a bot in which they can pass off to a human immediately, set your chatbots to only display during business hours when your entire team is there for instant chatbot-to-agent handoffs.
(ii) Display chatbots around the clock
Out of the pool of problems your customers have, there are some that are best suited for a talk with a human. Although that’s not as common as ‘reset my password. Team’s time is valuable, so save them for the justified issues. Let the chatbot take care of the simpler jobs like collecting basic info etc. Salesforce gives these entities: Text, DateTime, Date, Money, Number, Person, Location, Organization, Percent, Boolean, and Object (standard Salesforce or custom). You can form your custom entities as wanted.
It should be noted that the ROI is straightly associated with the extent to which the bot is used in the organization. The immense advantage of the bot is that it can be scaled for a minimal cost, so the more justified use of the bot, the better the ROI.
These are ways bots can benefit your business:-
- Automatically resolve top customer issues:
Keeping your top clients happy with your product or service is non-negotiable. Any brand that wants to improve and hold their customer base will prefer to rely on NLP and connected CRM data. It won’t just lessen the costs for the company but also help make the customer experience more authentic. To help its customers take benefit of the advances in AI, Salesforce has introduced Einstein Bots—AI-powered and CRM-connected chatbots—built natively on the Salesforce Platform.
- Collect customer data:
Consistent handoff to human agents when needed – Bots are supposed to be sharpened than humans, at least when it comes to particular tasks, They are designed to do some functions very well, and also can rapidly get lost when asked complex questions, While humans can understand complicated requests and non-standard language easily so it would be better if they hand off to human agents when needed. you don’t need to forget that bots can’t solve everything yet. Customer service with some uncommon questions being asked is still performed better by a real person.
- Effectively connect with business process:
Integrate bots to existing business processes to start actions by agents side – Organizations are already effectively using chatbots as an integral part of their customer contact strategy since chatbots are currently so advanced that they can successfully connect with business processes to automatically finish actions on agents’ behalf.
Build a CRM-powered Einstein chatbot
Now get ready to deliver an exceptional customer service experience around the clock. you simply just need to build your bot once and then deploy it across multiple channels like SMS chat and more.
Here how it works: First understand the most common types of questions your customers have for example – here you can see that the most common questions your Service agents address have to do with:- General, Queries, Issues Shipping. These are the areas where your bot can provide the most support.
Configure your Einstein Bot:
Now it’s time to create your custom chatbot. Use Einstein bot builder to create conversational flows that connect to your data in Salesforce and use natural language processing to better understand your customer’s requests.
Test and Deploy:
Next, it’s time to take it for a spin. Einstein lets you preview your bot and make sure everything is working properly before deploying it. Over time your bot will continue to become more accurate with every conversation.
And finally, Track your bot’s performance with built-in analytics. Measure metrics such as response time average handle time and other key factors to make sure things are on track.
Build a team to build your bot
The sort of a team that is required to build your bot is one that has articulated inspiring and differentiated vision. That can design experiences that are effective and delightful.
The following staff are must-haves:
- Product Owner: Identifies business use case for bots, convinces partners for investment & ensures all team members are working towards predefined problem statements. These following five are the main concern of the Product owner while building a bot:-
- What’s the issue and how will you overcome it?
- What is the Bot task?
- How will you design the bot?
- How will you know if the bot is effective?
- How will you launch the bot?
- System Administrator: Configures einstein bot dialogs in bot builder, coordinates bots with channels, incorporates bot with external systems, versions your bots & manages.
- Content Writer: One of the intriguing aspects of content writing for chatbots is the desire to move beyond writing for persuasion. The vital points while designing the conversations for your bot for advertising and communications (and some technical writing) are traditionally about conveying a brand voice and preferably soft-selling a product or service.
The AI behind a NLP based Bot:
Einstein Intent – The Einstein Intent API arranges unstructured content into user-defined labels to understand what users are attempting to say. Use the API to explore the text from emails, chats, or web forms to:
- Figure out which products prospects are interested in, and send customer requests to the appropriate salesperson.
- Route service cases to the right agents or departments, or offer self-service alternatives.
- Be aware of customer posts to present personalized self-service in your community.
Identify the Entities in a Body of Text: A component that automatically updates fields in CRM forms. The technique is similar to word classification, as users can classify words into pre-made categories (e.g., name, organization, URL, date, or phone number).
Setting up intent for your NLP Bot
Intents are the intentions of the end-user. There is four-level of placing intent in your NLP Bots.
1) Enable Dialog Intent
(i) Identify a list of Intents that you might want the NLP model to cover.
(ii) Tip: Start with a subset (10-15 intents), then start building more intents into the bot.
2) Add Utterances for Intent
(i) Input utterances to the intent
(ii) For best performance, each intent requires 150 utterances to train
(iii) Use of Intent Set from AppExchange
Tip: Avoid the Relatively Infrequent Term Confusion “RITZY” problem
3) Build AI Model
(i) Train the model after inputting the utterances for the intents
(ii) Review the Model Result under the “Model Management Page”
(iii) For Intent with low correctness (<80%), improve training data by adding more examples
Tip: Consider grouping intent that are ambiguous to each other
4) Test, Deploy & Iterate
(i) Prepare a list of utterances to test the Bots for different skills
(ii) Deploy the Bots in production for data collection
(iii) Use the data collected for iterate and improve the intent model for the Bot
Tip: Building an NLP Bot is an iterative process, plan for continuous review, and labeling of utterances gather from Bot in prod for continuous improvement.
Setting up NER for your NLP Bot
NER is a subtask of information extraction that seeks to locate and classify named entities in text into predefined categories it is essential to set up NER for NLP Bot because Chatbot NER helps you add more utilities to your Bot and ease out the process of detecting entities.
Out of the box vs custom entities
1) System Entity:
(i) Pre-trained Entities from NER Model
(ii) Predefined Entities: Object, Text
2) Custom Entity:
(i) Value Entities
(ii) Regex Entities
Roadmap: NLP Bots
Path to smarter NLP Bots,The key benefits of NLP Bots:-
- More positive results through accurate interpretation.
- Identify user input failures and resolve clashes utilizing statistical modeling.
- Use comprehensive communication for user responses.
- Learn quicker to address the development gaps.
- Accomplish natural language ability through lesser training data inputs.
- Ability to re-purpose the input training data for future leanings.
- Provide simple and basic corrective actions for false positives.
Next generation of text classification that supports multiple languages and OOD
Multilingual to Support Global Customers:
(i) New languages including French, Spanish, Portuguese, German, Italian, UK English are available in the summer20 Release
(ii) More languages including Chinese, Japanese are going to roll out in coming releases.
Automatic OOD Classification:-
Handle OOD Dialogue Without Training Data:
(i) Automatic classification of utterances into OOD if the intent is not defined
(ii) Common challenges in Bots to respond to customers OOD utterance appropriately
(iii) Customers do not need to provide additional training data for OOD utterances
Setup and Improve Languages Models Faster, It requires proper command with a large number of samples.
Feature: Recommends new inputs to train your NLP model from your chat transcript data
Why is that important: Reduce the work to come up with utterances for intent training
Use Cases: Setting up a new bot intent, improving the performance of an existing intent.
Get excited with Salesforce Einstein Bots for Service
Their quick start info provides you what you require to take the first steps to set up Einstein Bots in your Contact Center. For more info: Visit here
Resources and References
- The path to success: Salesforce Einstein Chatbot
- Explore how you can: Create a Basic Bot
- Build and manage: Einstein Bots
- Trailhead module: Set Up an Einstein Bot
- Learn: The Magic of Einstein Bot
- Explore a little more – Einstein Platform: Bots
- Evaluate: How Well Your Bots Understand Your Customers
- Add a new agent to the team: Activate or Deactivate Your Bot
- Entity – A critical element of the chatbot space: What’s an Entity?
- Einstein Bot dialogs: Understand Einstein Bot Dialogs
- Use Intents to recognize customers requests: Use Intents to Understand Your Customers
- Best Practices for Conversation Design: Conversation Design
- Monitor bot performance and view event logs: Monitor, Analyze, and Refine Bot Activity
- Telegram Chatbot: ChatBots for Telegram
- Facebook Chatbot: A state-of-the-art open-source chatbot
- Microsoft Chatbot: Build conversational experiences for your customers
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