Technological advancements are pushing customer expectations further and further into the stratosphere. The territory that was mainly uncharted a couple of years ago is now seeing a steep rise in development.
So what does this mean for sales leaders?
It means more data-driven decisions, more accurate forecasting, and, consequently, more customer wins.
All this and more is already possible with the help of artificial intelligence that can analyze your customer conversations, make educated predictions, and provide you with useful insights into each customer’s journey. Sounds like science-fiction, right? But this technology is now more available than you think!
So let’s dive into the topic that baffles a lot of non-technical users and explain a couple of crucial AI topics:
- Artificial Intelligence: Machine Learning & Natural Language Processing
- Conversational AI for Sales
- Benefits of AI for Sales
- Challenges Artificial Intelligence Faces
- Case Study: Unique’s Sales Intelligence
Conversational AI: Machine Learning & Natural Language Processing
Conversational AI works as a synthetic neural network that allows technology to understand, process, learn from, and respond to human interactions.
The concept of conversational artificial intelligence is closely connected to two other notions:
- Machine Learning. This is a vast field of computer science that is devoted to building machines that are capable of learning and improving through means of repetition.
- Natural Language Processing. This is a field of machine learning dedicated to interpreting and modeling languages so that software can interact with humans effectively.
It’s especially important to talk about conversational AI in terms of Natural Language Processing (NLP), as it explores how human language works and functions.
In 2022, thanks to the abundance of research projects taking place all over the globe, software engineers have an unsurpassed opportunity to tap into various studies and implement state-of-the-art advancements, like transformers, for instance, into their technology.
A transformer is a learning model that utilizes the mechanism of self-attention and differentiates the weight and significance of each part of the input data. These models work similarly to our brain, leveraging the power of a neural network of sorts that is trained with the help of all available data in the form of the written text.
This model learns to predict the next word based on billions of text patterns analyzed in the vastness of the Internet. Thus, the main purpose of the transformer is language modeling.
You can apply language models to different tasks in Natural Language Processing. However, since we’re focusing on the significance of artificial intelligence in sales, let’s explore it from the perspective of a platform that is able to catch essential data during client calls to further analyze it and provide you with data-driven insights.
Artificial Intelligence for Sales
Many sales-enablement technology providers already leverage the power of AI to decipher big amounts of data and extract useful insights.
At its essence, AI comprises in itself a number of various smart technologies like machine learning, computer vision, deep learning, NLP, etc.
However, when we’re talking about the relevance of AI in sales, we want to highlight the part of AI that uses superior computational firepower to analyze client conversations, a.k.a natural language processing. This technology helps salespeople deep dive into client data and performs certain cognitive tasks for them.
According to Salesforce's The State of Service report 77% of sales reps point out that automation software could help them complete more challenging tasks.
Additionally, even though only 21% of sales leaders admit to using AI today, its adoption is set to soar by 155% over the course of the next two years.
Salesforce also speculate that high-performing teams are almost 5 times more likely to be using AI than underperforming ones.
All this is due to the fact that AI is proactively helping companies supercharge lead volumes, improve client winning rates, and boost sales reps’ performance.
With the help of a combination of automation capabilities and useful insights, conversational AI takes sales daily routine to the next level, pivoting their focus to a whole new direction and giving them additional “superpowers” they could use to their advantage.
Benefits of AI in Sales
Now, let’s deep dive into the topic and discuss specific use cases for AI technologies in sales and what benefits they bring to the table.
CRM automation & call summary. Conversational AI is capable of extracting the most valuable information from the client conversation, analyzing it, and creating a custom summary for every call, recapping the most essential data.
Insights. It can also give you useful insights in real-time based on the agenda you chose. It will capture key deal moments live on the call and let you know when you need to mention some additional information.
Analytics. Artificial Intelligence can also analyze client conversations and inform you on key metrics like speaking time, sentiments, involvement rate, etc. By analyzing your sales calls, you can make improvements and adjustments for future client interactions.
Sales forecasting. Robust conversational AI technologies can aggregate enough data about each client, and based on it, predict deal outcomes and inform you about the best practices to use with each client in particular.
Customer-first approach. With the help of AI, you can research client data in-depth. Based on these insights, you can make more accurate predictions about the client, their needs, and pain points and improve your conversion rates dramatically.
Support for sales reps. Contrary to a common belief, AI is not attempting to completely replace sales representatives and certainly won’t do it in the near future. It plays the role of an insightful assistant that eases your workload.
Challenges Artificial Intelligence Faces
Artificial Intelligence is constantly evolving, which means that progress is tightly intertwined with new challenges.
Language input. Due to the general complexity of languages, it sometimes can be hard to extract meaning out of conversations where one thing can be said in multiple completely different ways. This poses a big generic challenge for NLP as the language models need extensive amounts of data to cope with this obstacle.
Data quality. When it comes to analyzing client conversations in real-time, data quality is key. It gets significantly more difficult for conversational AI to analyze the text extracted from video or audio of bad quality. Connection interruptions and gaps in conversations can decrease the readability of text extracted and pose challenges for AI.
Lack of resources. Even though there are multiple research studies on the topic of conversational AI published every now and then, some areas of AI remain mainly uncharted, and there might be little information you can actually tap into. This means that when you work with additional AI features, you have to pioneer your way to successful implementation.
GDPR. Robust data-based solutions use AI that needs to have access to information. Tons of information. This poses a challenge for software engineers in countries with strict data privacy regulations. However, there are multiple ways to make sure software complies with these regulations and doesn’t infringe on sensitive information without the client's consent.
Case Study: Unique’s Sales Intelligence
Here at Unique, we create AI-powered software to record, transcribe, and perform deep analysis of every client conversation live on the call. This gives our users an opportunity to receive important insights about each client, manage expectations, adjust their pitch, and build reliable forecasts about future deals.
Unique makes use of language models provided to us by Hugging Face to be able to classify data and create a summary for every client conversation. We combine all internal data within our organization with publicly available models, and it helps the technology to better process the data, classify, analyze and summarize it.
Unique’s Machine Learning Pipeline looks like this:
Basically, the process goes as follows: after the video is recorded, and transcribed, Unique then analyzes the text extracted from the conversation to accomplish three important tasks:
- Classify the text
- Create a call summary
- Extract data
Now let's discuss these three points in more detail:
Text Classification: thanks to the power of NLP, the Unique platform is able to classify the topic of the given conversation. For example., after processing this particular article, AI would be able to classify the topic as AI-related.
Moreover, Unique gathers the data detected during the call to perform the sentiment analysis of the conversation and point out high and low points in client negotiations.
In this particular case, the practical use for sales is the possibility to collect information about clients and structure it in a more efficient manner.
Call Summary: on top of text classification, Unique’s AI will summarize the information mentioned in the call based on the most crucial speech cues.
From a practical point of view, sales leaders and reps can quickly scan through the call recap, instead of rewatching or relistening the recording.
Data extraction: Unique extracts essential data that has been mentioned during the call to update CRMs for you.
This means that with the help of Unique, you can forget about taking notes during client calls and worrying about losing crucial information because Unique will make sure to save this data and update your CRM for you.
What’s more, Unique is striving to provide sales leaders with insights that facilitate revenue forecasting, so that companies can predict and anticipate deal outcomes and form a clearer picture about every deal and negotiation.
Artificial Intelligence Directly Impacts Your Efficiency
Technological progress behind AI mainly focuses on increasing human efficiency and providing fast and simple solutions to both individuals and corporations.
It gives humans superpowers to do more in less time. For sales leaders and reps, it can significantly improve performance and increase conversion rates. That’s why implementing an AI-based solution is the only right option in a very competitive environment.
By choosing Unique, you choose smarter decisions, more accurate forecasting, and positively impact your bottom line.