defining new normals in CRM - 4 trends in spotlight

Defining the new normal in CRM – 4 trends in the spotlight

Do you remember the times we used to go to our neighborhood mom and pop stores for some quick errands? The shopkeeper recognized and greeted us, enquired about our family’s well-being, offered the product we regularly bought, and if the product was unavailable at that moment, offered to deliver it at our house at no additional cost.

And he did that for all his regular customers.

An excellent way to establish rapport and nourish a healthy relationship with customers, through personalization.

That’s exactly what CRM is about in 2017, only businesses do it these days with the help of computers and internet, for millions of such customers. Today, customers not only knock business’ brick-and-mortar doors, but also, online – via social media, apps, websites, and the latest addition to the CRM kitty, chatbots.

What drives CRM in 2017?

Rise of the bots

Chatbots are perhaps the next big thing after apps. Every brand now has one in place – whether on its website or on social media sites such as Facebook Messenger. These bots act as lead generators, capturing customer queries and providing them quick information.

Here’s the Adidas Women UK Chatbot that promotes fitness among women and helps them book fitness sessions.

CRM

We spoke more about bots in our previous blogs, ‘Chatbots – a botched play or a game changer?’, and ‘Batman or Superman – What should your business’ chatbot be?

Smarter Mobile CRM

Mobile CRM is no longer just providing data on salesperson’s smartphones, online and offline. Some of the new features in Mobile CRM apps are:

  • Geolocation – Enables salesperson to identify which customers are in their vicinity, allowing them to drop by for quick, meaningful visits. This leads to effective usage of the salespersons work hours.
  • AI – Smart assistants pull customer data from their social profiles to glean a deeper understanding of customers. This helps the salesperson stay informed on the customer and personalize the pitch better.

Data-driven Personalization

Personalization is more than a “Hi *|FNAME|* ” in your mass mailers these days. Brands are leveraging machine learning to analyze customer data and identify patterns in behaviour. This helps them recommend the right products at the right time to the right customer.

For example, brands can use geofences to identify customers in store vicinity, pull their data from the CRM to analyze past purchases and push customized offer messages to their smartphones.

Leveraging Crowdsourcing

Business are deepening engagement with customers via crowdsourcing. Customers, ranging from various demographic segments are pulled together for surveys, polls, discussions, and online forums to provide feedback on new products, services and more. This helps customers feel more invested in the process, while it enables businesses to directly engage with customers and gain insights for their product roadmap.

A company that put crowdsourcing to good use is perhaps Lego Ideas. It is a website that acts as a forum for Lego fans to come together and suggest new Lego set ideas and designs. Have a look at their portal!

Lego Ideas - crowdsourcing

CRM has undergone a sea change in the last few years, and with technological advancements in AI and machine learning, the transformation will occur at an exponential rate. Businesses, globally, are recognizing the benefits of leveraging these advanced CRM features to create exceptional customer experiences, and widen mindshare as well as wallet share.

 

Automated CRM, powered by machine learning that helps your salespeople do what they do best. Score more deals. Contact AgilizTech to learn more.

 

Batman or Superman – What should your business’ chatbot be?

The Batman vs Superman battle continues, but this time in the realm of chatbots.

The dark knight is admired by many as he is the superhero sans any superpowers. He can’t fly, he doesn’t have immeasurable strength. But what he does have – excellent deduction skills, martial arts prowess and of course, tons of money. And in today’s world, Batman can exist.

Superman, on the other hand, is an extra-terrestrial messiah, who has extraordinary strength and can fly around (no thanks to the cape).

And when we take this analogy to chatbots, Batman is our trusted Retrieval model chatbot, while Superman is the Generative model.

We spoke about chatbots in our previous post, Chatbots – a botched play or a game changer?, and in this post, we dive a bit deeper.

Now what are retrieval and generative models?

Retrieval Chatbots

Retrieval chatbots can be understood in the form of a database and queries. There are scripted answers to scripted or near scripted questions. Let’s take an example.

Josh – the book recommending bot

Josh is a virtual assistant bot that suggests books depending on the genre entered by the user. Ben wants to gift his 9-year old niece a book. Watch how Ben (the user) interacts with Josh.

Retrieval Chatbot example - Josh

Here, the chatbot is retrieving titles as per the genres listed in its database and suggesting books to the user. This is a matching mechanism at work. A query is fired and that fetches a response from the database. Easy, peasy.

But many bots are failing this spectacularly, by not being able to tackle out of syllabus questions. Or not being able to empathize, to understand sarcasm or the worst of all, irony.

Retrieval bots are slowly improving and with breakthroughs in NLP, we might just be able to make them work better.

Generative Chatbots are different in the sense that they don’t follow the script.  They communicate with human users and learn to think on their feet and offer new lines.

Alice is an excellent example of an artificial intelligence bot that can have a fairly reasonable conversation with humans. No wonder, Alice won the Loebner prize thrice! Apple’s Siri is another amazing goal-based dialog agent. But these agents follow given heuristic patterns. Generative chatbots are those that use probabilistic techniques on existing data and create new lines. Deep Neural Network is the breakthrough technology that is helping shape generative chatbots, such as the LnH.

A Twitterbot , the LnH: The Band can compose on-demand new music based on the genre entered by the user. It has created 700 such new songs!

 

Let’s now look at another example of generative chatbots – Microsoft Tay. Tay, for those who aren’t aware, was the conversational AI chatbot that interacted with Twitter users and learnt with each tweet. It generated new content on its own, depending on what was tweeted to it. It was going pretty well, until people started training it to post racist comments.

A timeline view of Tay going from angelic to NSFW:

It becomes especially difficult when the chatbot has an open domain setting, that is, in the absence of a very specific goal. The chatbot cannot be programmed for just a few keywords and must communicate intelligently with the human on a larger set of topics. It sounds impossible, but research on deep learning is still on to make generative models work. The who’s who of the tech world – Google, Facebook, IBM and Microsoft – is piling up billions of dollars to solve the question mystifying us all – intelligence.

What chatbot should my business adopt?

It may seem like a fire or frying pan situation as Generative Chatbots are unpredictable and Retrieval Chatbots don’t know to handle irregular situations. So, the best solution, that businesses ideally ought to follow are a combination of Retrieval and Generative chatbots. Superman and Batman combined?

Excellent deduction plus massive strength?

Since that may be awhile in the oven, businesses are now going the retrieval mode. We looked at some of the top businesses out there using retrieval chatbots:

  1. Burberry

A renowned name in luxury fashion, they spare no expense for their bot, the Burberry Messenger Bot, either. Users can enter product keywords and browse through new products.

The chatbot displays a teaser video and provides a key button to touch. This speaks volumes of how the brand is trying to increase the bot’s appeal and thereby enhance customer engagement.

2. Dominos

A bigshot in the fast-food industry, Dominos helps its customers order pizzas using its chatbot for door delivery and carryout. The customer can now order via the Messenger chatbot and just pick up the order from the outlet when it is ready. The bot also offers order tracking facilities so that you don’t need to keep calling the delivery guy a hundred times.

 

3. Ebay

Conversational Commerce anyone? Ebay is on Messenger now, and it offers personal shopping assistance in the form of ShopBot.

Batman, that is, retrieval chatbot seems to be a safe bet – it is trained to answer specific questions and achieve a specific goal. You can be assured of not finding any grammatical errors, but be ready to face some annoyed customers when they at times it prompts “I am unable to understand that.”, or something of that sort. Retrieval chatbots do not yet possess artificial intelligence and it may seem like ‘the person is there but the lights are dim’. But the most important point is that they can be trained better using NLP and Machine Learning. Generative Chatbots are still not there yet. The work is on, and we are on the brink of technological advancements that can make these chatbots come alive with intelligence of their own.

At AgilizTech, we believe that chatbots are going to be the medium of B2C and B2B conversation in the near future. We’re exploring this exciting new realm of possibilities and are gearing up to leverage AI and Machine Learning to build revolutionary chatbots.

Chatbot

Chatbots – a botched play or a game changer?

A lot has been said and written about chatbots. After the Silicon Valley hype in 2016, the hue and cry over chatbots seems to have slightly died down now. Well, Facebook’s announcement of a 70% failure rate  dampened the expectations of most.  In fact, we tried a few of the bots on Facebook’s messenger bot platform, and while they were great initially, bots sometimes just don’t get it.

 

Microsoft’s Tay didn’t fare well either, with the bot running rogue on Twitter, sending out racist tweets after some of the users manipulated it. The other bots are in various stages of progress with majority of them not being able to process empathy, sarcasm and other everyday elements in human interaction.

Bots – the future of customer engagement

While Facebook’s announcement served as a major wake up call, the chatbots race is far from over. Gartner predicts that by 2020, customers will manage 85 percent of their relationship with a company without interacting with a single human. The era of Conversations as a Platform is rolling in. As Satya Nadella, CEO Microsoft said at the Toronto World Partner Conference event last year:

Chatbots fundamentally revolutionize how computing is experienced by everybody. Pretty much everyone today who’s building applications, whether they be desktop apps, or mobile apps, or websites, will build bots as the new interface.

Microsoft has certainly begun roll out, as could be seen on Skype. We spotted quite a few chatbots, ranging from weather, news, virtual assistant to games. To further prove that chatbots are far from over, Google has announced impetus to its AI and Machine Learning initiatives in the recently held Google I/O 2017 event. As more and more tech giants venture into the Chatbot landscape, the bot party is far from over. In fact, Markets and Markets estimates the Chatbots market to reach $ 3,172 Million by 2021.

How can businesses benefit from chatbots?

Omnichannel has been the war cry of businesses for a long time. Today, businesses connect with customers over websites, apps, social media, TV, Emails, etc. In the early 2000s, SMS was all the rage and businesses tapped it to engage with customers via notifications and promo ads. So heavy has been the onslaught that SMS is now perhaps experiencing the messaging equivalent of banner blindness. The latest medium to interact with customers, is where they spend the most of their time – Messaging platforms. Following the shift from SMSs to IMs, businesses can also jump onto the chatbot bandwagon to use messengers for customer interaction.

Three main ways in which businesses use chatbots:

Customer Support

Giving out routine information. Chatbots can dispense frequently asked information. Instead of flipping through FAQs, customers can quickly state their requirements and get answers from the bot.

Shopping Assistant

Helping customers discover and order products that best suits their needs. We used this Yatra Bot to check for flights tonight from Bangalore to New Delhi.

 

Payments

Helping make quick payments via secure gateways. Payjo is an Indian bot on Messenger that helps users recharge prepaid phones online and pay for DTH and postpaid bills via bot.

 

These are just three use cases of how businesses can use chatbots. There are hundreds of scenarios that are being tackled daily, with more bots joining the rank.

Benefits of using chatbots are:

  • Reduces manual efforts expended for routine tasks
  • 24×7 support made available to customers
  • Obtain more sales leads

 

While chatbots are in primitive state (as far as this technology is concerned) and need lots of improvement to be widely used, we are on the right path towards increased customer engagement. As AI technology develops, chatbots will have a better understanding of human nature and converse at par with humans. It is too early to say, but one day we just might be able to get them pass the Turing test with flying colors, and be worthy of the Loebner Prize.

At AgilizTech, we believe that chatbots are going to be the medium of B2C and B2B conversation in the near future. We’re exploring this exciting new realm of possibilities and are gearing up to leverage AI and Machine Learning to build revolutionary chatbots.