EIA - AI/ML DRIVEN CHATBOT- INCREASE YOUR PPC CONVERSION RATE

People may take different paths to reach the final step of purchasing. Most of them may follow the typical conversion funnel by starting at brand awareness and ending with a purchase.

However, there can be many different ways through which they pass through the sales funnel. If you can figure out those paths, you may be able to optimize them and improve your PPC conversion rate.

 TRY !!  EIA 

https://vimeo.com/411935645

ARTIFICIAL INTELLIGENCE DRIVEN CHATBOT:

https://www.techceptron.com/sales-and-customer

Google Analytics can show you the conversion flow, behavior, and acquisition. By going through this report, you can figure out the path which most of your shoppers are taking.

There may be different pages they are visiting before making a final purchase. Each of these pages should be optimized well so that the path is smooth for your customers.

It is also essential to take mobile devices and desktops into account to see which device is the most effective at generating sales. You can find this information through cross-device reports on Google AdWords.

The reports will also show you which channels are influencing their decisions to buy from you. Based on the results, you can accordingly improve the ones that are lagging behind and increase your PPC conversion rate.

Courtesy: https://www.spyfu.com/blog/good-ppc-conversion-rate/

Top AI-powered chatbots

Whether it’s on Facebook Messenger, their website, or even text messaging, more and more brands are leveraging chatbots to service their customers, market their brand, and even sell their products.

But even though most chatbots can handle moderately sophisticated conversations, like welcome conversations and product discovery interactions, the if/then logic that powers their conversational capabilities can be limiting. For instance, if a customer asks a unique yet pressing question that you didn’t account for when designing your chatbot’s logic, there’s no way it can answer their question, which hangs your customer out to dry and ultimately leaves them dissatisfied with your customer service.

Unlock tips, systems & recommended resources to stay ahead of the tech curve.

Fortunately, the next advancement in chatbot technology that can solve this problem is gaining steam -- AI-powered chatbots. By leveraging machine learning and natural language processing, AI-powered chatbots can understand the intent behind your customers’ requests, account for each customer’s entire conversation history when it interacts with them, and respond to their questions in a natural, human way.

If you’re currently using a standard chatbot, but want to upgrade to an AI-powered one, we’ve put together a list of the best AI chatbots for 2019. Read on to find the right one for you.

Best AI Chatbots

1. Watson Assistant
2. Bold360
3. Rulai
4. LivePerson
5. Inbenta
6. Ada
7. Vergic

1. Watson Assistant

Image Credit: IBM

Developed by one of the leaders in the AI space, IBM, Watson Assistant is one of the most advanced AI-powered chatbots on the market. Pre-trained with content from your specific industry, Watson Assistant can understand your historical chat or call logs, search for an answer in your knowledge base, ask customers for more clarity, direct them to human representatives, and even give you training recommendations to hone its conversational abilities.

Watson Assistant can run on your website, messaging channels, customer service tools, and mobile app. The chatbot also comes with a visual dialog editor, so you don’t need any coding experience to develop it.

2. Bold360

Image Credit: Bold360

Trusted by customers like Intuit, Edible Arrangements, and Vodafone, Bold360 patented its own natural language processing technology to help brands build chatbots that can understand your customers’ intent without the need of keyword matching and learn how to deliver the most accurate answers to them.

Bold360’s conversational AI can interpret complex language, remember the context of an entire conversation, and reply to customers with natural responses. Customers can even buy your products through the chatbot. You can also give your chatbot its own personality and run it on most messaging channels.

3. Rulai

Image Credit: Rulai

Armed with deep-learning based natural language understanding and adaptive multi-taking capabilities, Ruali, an AI-powered chatbot for enterprise brands, can understand the context of a conversation, predict user behavior, grasp customer preferences, take actions, switch to different tasks, and ask customers for more clarification.

Rulai also integrates with most messaging channels, customer service software, enterprise business software, and cloud storage platforms. You can either build a Ruali chatbot from scratch with its drag-and-drop design console and let its AI adapt to your customers or you can implement a pre-trained chatbot that has been fed data from your specific industry.

4. LivePerson

Image Credit: LivePerson

By collecting over 20 years of messaging transcript data and feeding it to their AI-powered chatbot, LivePerson can automate almost every industry’s messaging and integrate with most messaging channels like your website, mobile app, Apple Business Chat, text messaging, Google Rich Business messaging, Line, Facebook Messenger, WhatsApp, and Google AdLingo.

LivePerson’s BotStudio also lets you build chatbots from scratch, without any coding knowledge, and its analytics dashboard can track metrics like real-time sentiment, bot containment rate, bot conversation time, total conversation time, average order value, and bot contained sales, allowing you to grasp the impact your chatbot has had on your business’ bottom line.

5. Inbenta

Image Credit: Inbenta

Designed specifically for enterprise brands, Inbenta’s chatbot leverages machine learning and its own natural language processing engine to detect the context of each customer conversation and accurately answer their questions. Inbenta also offers a dialog manager, which allows you to craft custom conversation flows and paths.

Additionally, when Inbenta’s chatbot realizes that one of your customers needs to talk to a human, it’ll escalate the conversation to the appropriate support agent. To make your chatbot seem more human, you create a custom avatar for it, too.

6. Ada

Image Credit: Ada

Trusted by customers like Medium, Shopify, and MailChimp, Ada is an AI-powered chatbot that features a drag-and-drop builder that you can use to train it, add GIFs to certain messages, and store customer data.

Ada can also integrate with most messaging channels and customer service software, send personalized content to your customers, ask for customer feedback, and report on your bots’ time, effort, and cost savings. According to their website, Ada has saved their customers over $100 million in savings and 1 billion minutes of customer service effort.

7. Vergic

Image Credit: Vergic

Vergic offers an AI-powered chatbot that can serve as your businesses’ first line of customer support, handle transactional chats, and transfer more complicated problems to your actual customer service agents. It’s like a hybrid chatbot that can boost your employees’ productivity.

By leveraging natural language processing and natural language understanding, Vergic can also perform sentiment analysis, share documents, highlight pages, manage conversational workflows, and report on chatbot analytics.

Streamline the Recruitment process by AI Chatbot - EIA

Qualifying candidates with a recruitment chatbot: New way of filtering candidate and streamline recruitment process

Web: https://www.techceptron.com Linkedin: https://www.linkedin.com/company/techceptron/ Facebook: https://www.facebook.com/techceptron/ Twitter: https://twitter.com/techceptron

To solve our client's challenges, we needed a recruitment chatbot that

qualifies candidates earlier on in their application journey,

prioritise the number of CVs that land on the team's desk, and,

provides an experience that reflects our client's values.

Qualifying candidates through a conversation

The recruitment process at a mid-size company with this many vacancies and this much applicant traffic is complex.

We encouraged our client to break down the solution and start small.

The first iteration of their recruitment chatbot would take each candidate through a conversation covering 10 to 15 topics. With each question, the chatbot gathers data on the candidates' skills, previous experience, and qualifications.

For each vacancy, our client is able to set a series of requirements such as driver's license or work-related certifications.

Throughout the conversation, the chatbot qualifies each candidates before they move on to the next phase. If they do move to the next phase, the profile handed over to the recruitment team is filled up with up-to-date, relevant, and accurate information.

This conversational approach to recruitment also allows our clients to extract the information they require from applicants. While applicants might skilfully skip over disclosing a lack of qualification in their CV or cover letter, the chatbot requires it to move forward. This alone prevents the recruitment process from clogging up with candidates unlikely to get through to the end – saving everyone involved a lot of time.

Solving the challenges internally

Our client, like many well-thought-out organisations, follows a promote from within policy. This presented as a fantastic opportunity to follow our preferred chatbot implementation path; starting with a proof of concept. With this approach, we got to target 30% of our client’s applicants.

To browse and apply to open positions, employees simply access their internal HR portal. Deploying the first phase of the solution internally allows us to test the technology and tweak its features, all the while reducing the risk associated with adopting a new technology.

Making sure their values and culture transpires within the chatbot was a priority for them, and testing internally proved to be the best route.

The results: prioritised and qualified candidates

As always, we started this project with a proof of concept. This particular one was two-fold.

First, the EIA chatbot had just enough built-in features to be operative. It was important to put something together that works without spending five or six months in development.

Second, the chatbot was released to subset of the target market -- their own employees.

Our clients achieved a 73% reduction in unqualified applications. Even with the reduced audience, this translated in significant time saving within the recruitment team.

The recruitment team deemed the time they spent sifting through candidates pre-qualified by the chatbot as 'a lot more productive'.

Finally, we built a feedback feature into the chatbot, allowing each applicant to review their experience (whether their application was successful or not). 92% of applicants marked themselves as 'very satisfied' with this new process. We did not let the process define the experience, instead allowing the experience to define the process; and clearly this resonated with the applicants.

The results of this proof of concept exceeded expectations. Both the recruitment team and the candidates experienced a smoother, faster, more targeted process.

The success of this first iteration encouraged our clients to expand on the project, soon opening the job application experience to external applicants.

Best wishes, Smriti Tripathi Head - Corporate strategy Techceptron Technology Pvt. Ltd. A-302, Binawat Majestic Hadapsar,Pune,Maharashtra Email:smriti.tripathi@techceptron.com Web: https://www.techceptron.com Linkedin: https://www.linkedin.com/company/techceptron/ Facebook: https://www.facebook.com/techceptron/ Twitter: https://twitter.com/techceptron

HOW EIA- AI BASED CHATBOT EMPOWERED BUSINESS?

#techceptron #customerservice #customersatisfaction #customercare

Have you ever thought of implementing AI Chatbot as a sales or customer service channel to boost sales and customer support ? I’m pretty sure we could be of help here.

Let me introduce EIA (Enterprise Intelligent Assistant)!!

EIA is Artificial Intelligence based Chatbot!!!

HOW EIA EMPOWERED BUSINESS?

1) Lead Generation

2) Enhance Customer Support

3) Notify Customers about latest Collection and offers

4) Quick find Items

5) Track and Manage Shipping Information

6) Process Order

7) Product Recommendation

8) Provide Promotions

9) Give wings to your existing Payment Process

10) Higher open rates and click rates: We have been seeing 80% open rates and 50% click rates

More opportunity to have a conversation with potential customers and close sale: This is basically inside sales,

but on chatbot, where more people are likely to interact with you because texting is low friction and a sticky habit:)

Since there are quite a lot of opportunities with AI chatbots, then I’d like to suggest that we meet?

Shoot email: smriti.tripathi@techceptron.com

Web: https://lnkd.in/gCRsQdD

Linkedin: https://lnkd.in/gkB5TMb

Facebook: https://lnkd.in/gqjxY4s

Twitter: https://lnkd.in/gjC_Rcz

How to Build a Chatbot from Pitch to Promotion

www.techceptron.com 

How to Build a Chatbot from Pitch to Promotion

1) Decide your bot's purpose.

Ultimately, the purpose of a bot is to provide a service people actually want to use -- time and time again. No bot is meant to do everything, so when you set out to create your own, think of an existing problem that it can fix in a more efficient way.

While there are many types of chatbots, if you’re building one for the first time, you’ll likely want to choose from the following two options:

Informational bots

As the name suggests, these bots provide users with a new format of information consumption. For example, breaking news bots send developing stories as the information becomes available. TechCrunch has a bot of that nature -- check it out below:

Utility bots

These bots are automated to complete tasks and answer questions. In other words, they solve a user’s problem or inquiry via a chat transaction. Customer service bots might immediately come to mind here, but a growing number of utility bots are being built for purposes like booking appointments or shopping online. One of our personal favorites is TacoBot: Taco Bell’s still-in-development bot that allows people to order food via Slack. Join the waitlist here, and check out the preview:

2) Decide what messaging app your bot will live on.

Earlier, we provided examples of bots that live on Messenger and Slack, respectively. And while those are two very popular options, there are many more available -- for example, Kik and Viber.

Your chatbot’s “home” will largely depend on who’s using what. You’ll want to aim for the apps with an audience that matches the one you’re trying to reach. Slack, for example, tends to be more business-focused, so productivity bots are particularly helpful there.

Sephora is a great example. While the brand has bots on both Messenger and Kik, each one functions differently. The Messenger version is used for customer service, feedback, and booking makeovers:

The Kik version, on the other hand, is designed to help users find products and makeup tips:

3) Decide which platform you’ll use to build the chatbot.

Most messenger apps have tools and documents to help developers build bots -- for example, Messenger has an entire library of resources here.

However, there are numerous platforms that can also help you build your bot -- in some cases, without a lot of coding required. Here are a few that we recommend:

1. Motion AI
2. Chatfuel
3. Botsify
4. Beep Boop
5. Bot Kit
6. Octane.ai

4) Create your bot’s personality.

Remember when we mentioned the importance of matching your bot’s home with the audience you’re trying to reach? Well, we have a similar guiding principle for your bot's personality: It should match your brand.

One of our favorite examples here is Pegg, a financial assistant designed for startups and small businesses -- but speaking as someone who recently returned from vacation, it’s helpful for anyone trying to track their spending. And while finance isn’t something that’s usually associated with a fun, playful voice, Pegg’s bot, HelloPegg, flips that connotation on its head with a cute logo and friendly voice.

5) Build your bot’s flow.

When you begin creating your chatbot, the platform you’re using should provide options on how to build out conversations. Usually, this is by way of providing the user with drag-and-drop or multiple choice responses, or frontloading the bot with if/then statements. For example, with the HelloPegg app above, the if/then flow might look like this:

If the user begins the sentence with, “Spent” -- then respond with, “Who did you pay?”

It’s a way of building a series of questions that are dependent on certain input criteria from the user to reach a given response or solution. Remember, a bot is supposed to be able to understand intent and deliver a solution in the most efficient way possible -- that's the main point of building a conversational strategy. Unlike a type form, for example, not every user can receive the same questions, and each answer the user gives should alter the following question to make the conversation as productive as possible.

Chatbots don't necessarily need to be loquacious -- they serve the purpose solving real problems from real people with the same (or better) ability as a human.

Things like buttons, cards, or other UI elements can be helpful here. For example, when chatting with a friend on Messenger, you might notice that the app prompts you to do certain things, depending on what you’ve typed in -- like when I used it to wish my colleague, Eric Peters, a happy birthday.

To help you build out these various pieces, we created the conversational framework below.

Finally, you’ll need to set up your chatbot’s ability to process the natural language that most users will input -- meaning, the conversational vernacular that we use day-to-day. For example, "People don't typically chat using words like 'affirmative' and 'negative'," explains HubSpot Senior Manager of Web Development Dmitry Shamis. "They say things like 'yup' and 'nah, playa' so natural language processing allows your bot to understand the underlying message and sentiment of those words."

The way to do this varies with each platform, so depending on what you’re using to create the bot, going about this step will vary.

6) Connect the bot to the messaging app.

Once you’ve reached this step, you’ve likely finished building your bot. Now, it’s time to connect it to the app where you want it to live.

Many of the resources we listed in section 3 will allow you to do this within the same platform you used to build the bot. Both Motion AI and Chatfuel, for instance, have buttons in the interface that allow you to simply attach your bot directly to your Messenger page. But before you commit to those options, make sure you do thorough research to make sure you won't be expected to pay any fees to the platform in the case that your bot sees a high level of success.

There are a few tools available to help you do this, one of which is the Recast.ai Bot Connector. It’s integrated with a number of apps, including Kik, Messenger, and Slack. It’s open source and free -- check out the instructions for getting started here.

7) Test and train with a beta group.

I don’t know about you, but when I’ve finished a project of which I’m particularly proud, I’m impatient to share it with the world. But as much as we want to get our work out into the hands of the adoring masses, it’s imperative to make sure it works -- especially with something as highly customer-facing and interacting as a chatbot.

That’s why we recommend forming a beta group to test the bot before it’s launched for public consumption. That can be internal or external -- here at HubSpot, for example, we often test new products and features by sharing them with our colleagues and asking them to check for functionality, quality, and bugs.

But whoever you choose to test your chatbot, make sure they’re not afraid to give you their honest feedback. In order to fix a mistake, it needs to be unabashedly pointed out to you first.

8) Promote your chatbot.

Once your chatbot has been thoroughly QA’d and de-bugged, it’s time to release it to the public -- and, of course, promote it.

There are several ways to go about the latter, but for the sake of keeping your strategy focused, we recommend the following steps to get started.

Add it to chatbot directories and catalogs.

Not every app will have a listing like this, but if you’re using one that does, make sure your app is included. (For example, here’s Slack’s.) Otherwise, look to third-party directories like BotList or Bot Finder for such listings.

Create a dedicated, SEO-friendly landing page.

For us, there’s often nothing more frustrating than catching wind of a great chatbot and being unable to find a dedicated website for it. That’s why we encourage you to create a dedicated, central page to explain the purpose, features, and where to find/install your chatbot to avoid any difficulty finding it, or other confusion.

TOPBOTS marketing and strategy specialist Adelyn Zhou emphasizes the importance of such a page. “A dedicated landing page for your bot gives users the option to first read and understand your distinct value add,” she writes on Medium. “Without the introduction, you’re leaving them to deduce your functionality by themselves.”

Include a messaging option in your emails.

Many emails include CTAs and icons for the reader to follow the sender on social media. Now, you can also add an option for your audience to engage with you via chatbot, by including icons for Messenger and Slack, for example.

Continuing the Conversation

Before you begin, remember: The hardest part of this process is not building your chatbot.

It may sound counter-intuitive, but if you re-read the steps above, you’ll see that while the actual bot buildout isn’t without its challenges, it doesn’t present the most difficulty. Rather, the hardest part is improving your conversational marketing strategy over time -- based on how actual humans are interacting with your bot.

Even after you’ve completed the steps we’ve outlined, your work won’t be completely done. You’ll want to see how users are engaging with your chatbot, and if they’re not, what might be the cause of it. Is it truly addressing the problem it was built to solve? Has it turned out that your audience has other issues it wishes to resolve with a bot?

Think about these different factors once your chatbot goes live, and the various ways you can continue to make it even better.

Source: HUBSpot