Artificial intelligence (AI) and machine learning are changing the ways that businesses operate. It is creating an automation revolution. By this year, 30% of B2B businesses are expected to use some form of AI to empower some part of their sales process.
There are several significant trends and technologies spurred on by the growing sophistication of machine learning technology. The engineering process of chatbots to make machine learning possible uniquely brings a new aspect to the sales funnel. Arguably the most popular and substantial of these trends is the rise of chatbots.
According to a report by WordStream, 87% of online marketers utilize video marketing. With the advent of smartphones, the traditional long-form sales pages and emails are being supplemented with short video marketing. The small screens make reading lengthy promotional pieces cumbersome and difficult for some.
Theatrical quality videos are not required to make an effective marketing video. If you spend any time on social media websites, you are aware of how dominant video has become online. There has also been a surge of paid video ads shot using handheld mobile devices.
Top social media websites that feature options for video are:
- YouTube
Why are chatbots so popular? It’s simple: chatbots can enhance a sales process, improve the customer experience and create an overall tighter and faster marketing funnel.
How Machine Learning Works In Chatbots
At the core of chatbots is the AI engine that allows for machine learning. Through simple user inputs, machine learning allows chatbots to grow their understanding of semantics, tone, sarcasm and many of the other difficult intricacies of language.
In other words, the more conversations a chatbot has with humans, the more it learns and the greater its sophistication becomes. More conversations means more data and that’s the fuel that powers the AI engine inside these programs.
Chatbots don’t rely solely on textual data but also user data. Specially, what interactions the user has before and after engaging with a chatbot.
- Pre-chatbot data is used to filter the responses and content provided by the chatbot to the user.
- Post-chatbot interactions allow the chatbot to gauge its own efforts. If it connected the user to the right information that led to a sale or conversion, the chatbot knows it did its job. Otherwise, it looks for signals to refine its strategy for future conversations.
What Goes Into Engineering A Chatbot?
Building a chatbot from the ground-up is a massive undertaking that requires sophisticated engineering, which is why many businesses don’t explore the possibility of adding such a tool to their sales process.
Luckily, there are a number of solutions that offer the framework of a chatbot.
However, these packaged chatbot solutions are not immediately ready-to-go. The bones are there, but not the heart and soul that make an effective conversationalist. There are several criteria that an effective chatbot must possess:
- Use of short, concise responses that effectively answer user inputs
- Simple language to ensure user understanding
- Adapt to the customer’s language
- Ability to segment users (first-timers, return visitors and frequent customers)
- Avoid gibberish or irrelevant responses by asking for more details
- Empathic and ability to create a connection
- Connected to content and materials that fuel marketing funnel
Some of these points take time to develop, while others will be built into the algorithm of your chatbot.
Subtlety Is Key For Chatbots Facilitating Sales
The best chatbots work very subtly. Ideally, customers don’t even realize that they are talking to a machine learning tool! And, they feel helped, not sold too. Thus, chatbots also have to work subtly in their aim to facilitate the sales process.
The concept of growth marketing is strongly focused on data and how to use it to convert more prospects and drive sales. The growth marketer utilizes any and all data they have at their disposal to build demand and drive sales. The process takes a lot of experimentation to determine the best approach.
You can invest in growth marketing techniques to gain insight on how to best engage with your prospects and client base. In times like the pandemic lockdown, data will help you see how the tendencies of your customer base have changed and how you can best address the new dynamics.
If users feel too sold too by a chatbot, it creates a negative experience. It’s about providing service that helps them convert faster, rather than push sales immediately. Chatbots achieve this objective through a variety of techniques.
- Helping customers make up their mind and reach a decision — RapidMiner removed every lead capture form on their website and replaced them with chatbots. The objective was to use automated conversations to qualify leads and help direct people to the sales team that are expressly interested in RapidMiner’s solution. The chatbot was responsible for 10% of all new sales and created thousands of leads for the sales team.
- Analyzing and identifying funnel positions and providing results to match — Essentially, RapidMiner’s chatbot was able to filter traffic based on the reason that a visitor arrived at the website, whether he or she was exploring the product for the first time, answering a technical support question or talking to someone in sales. By establishing these distinctions, the chatbot was able to segment traffic more efficiently and send only the most qualified leads to the sales team, thereby saving them the time and hassle of handling requests from unqualified persons.
- Creating the appearance of a larger sales team — Anymail finder, an SaaS email verification software startup, realized that 90% of their big buyers were using the chat function before making a decision. But, the two-person team struggled to respond to every request. Introducing a chatbot equipped with answers to the most commonly asked questions gave Anymail finder the appearance of a large support department and encouraged more purchases from this important segment.
- Offering resources that help leads make up their mind — Part of Anymail finder’s success was creating content that answered those commonly asked questions. These detailed articles were included in the chatbots responses. And, when visitors reached these content assets organically, they received an automated chat message unique to that page.
Conclusions
The popularity of chatbots for B2B marketing teams demonstrates a shift in the way these companies attract and generate sales. There is an overwhelming majority, around 80%, of B2B marketing executives planning for an AI revolution. Chatbots are at the forefront of this change because of how they facilitate faster sales and generate more qualified leads. The objective is to do more with less and chatbots achieve this goal effortlessly!
