Conversational AI

Artificial Intelligence for Sales Teams (Sales AI): Benefits, Use-cases, Future & more

Artificial intelligence (AI) in selling has changed the form and function of the sales department for good. AI is changing how sales reps contemplate every part of the cycle, from the first interaction to the end close.

Traditionally, B2B sales teams worked in a linear manner. 

Suppose a sales professional wants to pile up a list of leads of an addressable market for an upcoming campaign.

With no technology at their disposal, the representative had to manually compile the list, which took endless hours and effort. Not to mention the hard work consumed in conducting research before reaching out to prospects.

However, this cumbersome approach has some caveats. First, sales teams cannot determine how to identify or prioritize high-quality leads.

Moreover, despite having raw insights, they cannot turn that data into intelligence that can help improve conversion rates and customer experience.

AI for B2B sales enables salespeople to operate with detailed assessments based on the most up-to-the-minute information. 

Whether compiling prospects’ data, refining ideal customer profiles (ICP), or figuring out action items – the AI’s analytical strength continually improves sales efficiency. 

According to Gartner, by 2025, 3/4 of B2B sales organizations will refine their old strategies with AI-based sales assistants and solutions.


What Is AI (Artificial Intelligence) for Sales?

AI sales platforms combine human and machine intelligence to stave off guesswork from digital-first sales cycles and convert multi-variate datasets into actionable intelligence.

AI-based sales tech creates statistical models using multiple sales data – prospects’ information, speech/text communication, and salesperson activity. Then, it identifies patterns and makes predictions without human intervention.

Types of AI Applications for Sales and How They Work

AI sales platforms strengthen B2B salespeople’s potential to achieve maximum acceleration towards bigger revenue goals. 

The following round-up discusses various AI technology subsets and their usage in sales.

1. Chatbots

AI chatbots steer interactions with prospects via emails, messaging apps, and websites using text or text-to-speech.

With these virtual assistants, sales agents can respond quickly to customer queries and engage them with the perfect message. 

As such, sales pipelines get a much-needed boost and brim with potential buyers that companies deserve. By 2027, global investments in chatbots will hit around US$450 million – almost 11X up from the 2018 levels.

2. Machine Learning

Machine learning (ML) uses algorithms to analyze patterns from every touchpoint of buyers’ behavior – website visits, social media engagements, search histories, and more. 

These ML algorithms then decrypt the buyer behavioral trends and make predictions and sales forecasts without any manual programming. 

Including ML in the sales tech stack helps salespeople maximize their acceleration toward revenue goals.

3. Augmented Analytics

Augmented analytics provides a complete picture of prospects in a flash.

With it, sales teams can establish key performance indicators (KPIs), including the number of online web visits or ongoing purchases and the average call and message count delivered in a quarter. 

Not only does this accelerate the process of devising upsell/cross-sell campaigns, but it also fixes potentially hidden problems before they intensify.

4. Natural Language Processing (NLP)

Natural language processing (NLP) assesses the sentiments and tones of prospects’ inputs. NLP filters quality leads and eliminates the headache of dealing with unqualified leads, thus saving time and boosting efficiency. 

Furthermore, the data gathered from NLP helps sales reps determine the exact location of leads in the sales funnel and tailor their cold pitching accordingly.

5. AI Visualization

AI visualization utilizes algorithms to provide B2B sales teams with buyers’ or prospects’ data in a graphical format that is more accurate and easier to understand. 

Based on the pictorial data, sales reps look for relationships between different variables and identify trends, patterns, and anomalies in data. 

They can, for instance, conclude whether a particular offering is resonating well with website visitors.

AI for Sales and Marketing Use Cases

1. Sales Attribution

AI-based assistants enable salespeople to deal with big data to attribute results with greater precision. Consequently, they can single out the customers and campaigns most effective at improving ROI. 

Having that considered, several sales processes might happen beyond companies’ customer relationship management (CRM) systems. Hence, such activities will not appear in their CRM data unless salespeople do not forget to log them. 

Fortunately, AI automatically logs all sales reps’ activities and then ties them with the right opportunity.

2. Lead Scoring

Lead scoring and nurturing depend heavily on NLP and natural language generation (NLG) to help improve each prospect’s score.

These AI technologies deduce patterns from prospects’ profiles, their online activities, and previous interactions in the form of emails or social media posts. 

Then, the algorithms rank leads and identify sales-qualified leads (SQL), thus strengthening sales pipelines and logical decision-making.  

3. Lead Generation

While the human factor will always exist in lead generation, AI streamlines the task by helping salespeople contact the addressable market.

It uses neural networks to segment buyer personas as well as upload their complete information to a single database. Salespeople can thus reach out to their target audience with minimal effort.

4. Sentiment Analysis

AI sales platforms not only transcribe customer-facing calls in real time but also observe the sentiments of potential leads.

Equipped with this sentiment analysis, sales executives can easily track dozens, or even hundreds, of active calls and instantly pinpoint those reflecting negative sentiments. 

If they find any, they can unfold the real-time transcripts, skim them to get more context, and take further actions to save a deal accordingly.

5. Personalized Experiences

Using prescriptive analytics, AI-guided selling provides recommendations to salespeople regarding which deal to close at what price (and how) based on prospects’ historical data. 

Such insights are beneficial when deciding how to engage with leads. They provide reps with opportunities to personalize their communication strategy and map to prospects’ or customers’ expectations.

Recommended Read: The Ultimate Sales Toolkit for a Modern Sales Team!

5 Best Benefits of Using AI for B2B Sales

1. Suggest Ideal Prices for Deals

Determining reasonable pricing for every B2B client is tricky, but AI makes it significantly easier. 

It uses algorithms to crunch all prospects’ details – location, size, and previous successful deals – and accordingly suggest an optimal price for each proposal. 

Optimal pricing slashes negotiation time and improves the odds of conversions manifold. Besides keeping pace with customer expectations, ideal pricing makes sure the expected margins are not disturbed.

2. Easier Upselling/Cross-Selling

Upselling and cross-selling are the centerpieces for sales teams. AI for sales has been essential in developing recommender systems based on collaborative and content-centered filtering. 

The technology clusters prospects based on their demographic, psychographic, and geographic backgrounds, enabling salespeople to generate personalized offers and product (or solution) recommendations.

3. Training at Scale

AI sales platforms help salespeople with their pitches by offering individualized analyses. Sales leaders can then use these analyses for one-to-one coaching of sales reps. 

For instance, if a salesperson struggles with certain aspects during cold calling, speech analytics will underline particular areas of improvement. 

As such, salespersons can receive training accordingly, which will help them identify their weak spots and eventually rectify them.

4. Keep Customers at the Center

Collecting insights on prospects, writing cold emails, and maintaining databases – these are all a part of everyday tasks. But they also keep salespeople busy in low-value activities and deviate them from what matters the most.

With artificial intelligence for sales leads, sales teams can gather prospects’ complete details – including contact data, addresses, and current companies – within a few clicks. 

Process automation encourages sales teams to focus more on the essential aspect  – i.e., the customers. It keeps them off the activities that have relatively lower returns. It helps them prioritize customers at the very top.

5. More Accurate Sales Projections

While humans are proficient in projecting sales figures and goal-setting, AI helps them do this with more accuracy. Advanced analytics provides sales leaders with a holistic view before making a sales projection. 

From this, the C-suite can make more informed mission-critical decisions. For instance, monitoring the peak hours in call centers can help with future onboarding.

Challenges of Adopting AI for Sales Training

1. Lack of Data

For an organization to achieve the most timely and efficient AI strategy for sales and marketing, it must have a reliable source of high-quality data that are accessible, secured, and well-governed.

Unfortunately, businesses assume they don’t have the right data sets, or they’re unable to present large amounts of data in a suitable format to configure AI algorithms.

2. Outdated Infrastructure

AI systems require premium processing capabilities and suitable infrastructure to achieve high internet speeds. Organizations that adopt AI for sales management must be willing to take their IT services to the next level.

Most companies still rely on traditional legacy systems and outdated infrastructure to run their IT operations due to the costs involved in updating the systems.

3. Lack of Skilled Staff

Being a sophisticated algorithm, AI software for sales requires special skillsets and expertise for implementation and deployment. Many organizations lack knowledge in software optimization, data management, and integration.

This prevents companies from adopting AI technologies seamlessly and obstructs them on their AI journey. Companies must allocate additional budgets for AI app development training.   

4. Data Storage and Security

As huge amounts of data are used to enhance AI efficiency, it creates data security and storage issues.

The higher the data generated and the higher the number of users who have access, the higher will be the possibility of data leakage on the dark web.

Companies must maintain an excellent data management environment for training AI algorithms.

5. Rare and Expensive

Hiring a data engineer and a data scientist with the required skill set and expertise is expensive. Plus, finding a high-end specialist to conduct AI training is not easy.

This is one of the main challenges that organizations with a small budget face quite often.

The Potential Future of AI for Sales

Source

Companies across the globe are witnessing how AI for sales management has enabled sales teams to concentrate on building relationships instead of crunching numbers or entering data.

Is your organization ready for what AI for sales and marketing could do in the future?

By taking care of a series of sales-related tasks, AI for B2B sales is already changing the sales process in 2023. Wondering how? The following are 6 ways in which AI can impact sales in the future:

1. Easy Lead Generation

Lead generation is one of the major challenges sales teams face.

An AI strategy for sales and marketing can make it easier to find leads by analyzing website visitors, tracking leads who interact with content, and searching for the most valuable leads.

Chatbots and CRMs are popular AI-powered automation tools that help in lead generation and automatic lead assignment to a salesperson.

This not only saves marketing and sales teams time but also generates better-quality leads.

According to a Gartner survey, 75% of B2B sales organizations will adapt to both traditional and AI sales solutions by 2025. Further, as per Techsur’s research, nearly 87% of existing AI-using companies plan to adopt AI for sales forecasting.  

In the coming years, AI will be able to generate new leads, nurture them, and even schedule sales calls – eliminating the need for human interaction.

3. Optimize Lead Qualifying

Imagine spending less time sorting and generating leads and more time closing deals. Sounds amazing, isn’t it? That’s exactly what AI can do. AI can simplify the lead-qualifying process.

For instance, chatbots can raise questions to qualify leads, enabling the sales team to concentrate on leads within their company’s audience.

Consumer support bots can forward resources to enhance prospects’ knowledge and resolve queries so that the sales team can concentrate on closing the deals.

Furthermore, marketing teams can adopt AI for the lead-qualifying process by utilizing AI-powered triggers that will propel prospects further down the sales funnel.    

4. Analyze Lead Behavior

Understanding lead behavior helps in identifying which prospect is close to conversion and the prospect’s position in the sales funnel.  

AI technology equips the sales team with extremely detailed statistics about lead behavior, like the webpages visited by them, the time spent reading a blog or article, etc.

This data automatically creates a sales report that enables sales managers to analyze the lead and salespeople’s performance. By spending less time on data generation, salespeople and sales managers can focus more on their customers.

5. Enhance Lead Support without Missing Out on Personal Touch

With time, chatbots have incredibly improved at comprehending natural language patterns. They’ve become more conversational, ensuring prospects receive the required assistance without getting stuck with pre-programmed responses.

AI chatbots can do a lot more than this. They can explain complex issues, tell stories, and provide a quote or direct leads to the correct department.

By listening to sales calls, AI can help augment conversion rates by providing details the sales team requires to close more deals.

With the help of these additional details, sales reps can have a better customer understanding, enabling them to provide relevant offers and information.    

6. Create Sales Contracts

Preparing sales contracts is a time-consuming process that requires special focus on every minute detail.

An AI program can scrutinize chat conversations, emails, and sales call to generate a sales contract depending on agreements the sales rep and the customer already made.

In addition to preparing contracts, AI software for contract management can highlight sections that require to be negotiated, pull renewal dates, and organize details in a better way to avoid contract disputes.

This streamlines the contract workflow, enabling the legal and sales team to concentrate on bigger problems instead of spending hours on contract negotiations.

7. Optimize Digital Workflows

AI for sales data can streamline the digital workflow by automating sales reporting and performing other critical sales tasks. For instance, an SDR AI bot can assign leads, update the CRM, and even create follow-ups.  

By taking over appointment setting, data entry, and reporting, using AI for sales calls enables sellers to concentrate more on trying to understand their prospects and prepare for meetings.

It also gives sales reps more time to focus on negotiating, building better customer relationships, and closing deals.

Will AI And Machine Learning Replace Sales Jobs?

It’s quite evident that the use of AI for sales data has transformed the way sales teams work. But it wouldn’t be apt to say that AI-powered tools will replace salespeople.

These tools generally augment human sales reps and take over work they don’t have the time or ability to perform.

For example, AI tools for sales can interact with prospects without human intervention to arrange two-way conversations with them. Rather than missing out on leads, they contact each lead, nurture them and try to qualify them.

Once the lead requires human attention, the tool directs them to the sales team. Thus, it would be safe to say that AI software for sales bestows the sales team with superpowers rather than replacing them.     

AI-Powered Social Selling

AI can be used to enhance social media marketing. By tracking data on users’ behavior, demographics, and interests, AI algorithms help companies find prospects and deliver ads to them on their preferred platforms.

This not only helps in conveying ads to the right people but also brings down advertising costs by preventing targeting the ones who are unlikely to be interested in the service or product.

Sentiment analysis is another AI technique that utilizes NLP to identify a text’s emotional tone.

This enables companies to analyze social media conversations and recognize trends and patterns that shape their brand’s image, giving them insights into how their brand is being perceived and helping them determine the areas that require improvement.

AI-powered tools also help improve the effectiveness of social media marketing by scheduling social media posts beforehand, creating new content, and saving regularly used captions and hashtags. This enables companies to save time and concentrate on engaging with their customers.

With deep learning AI algorithms, companies can create customized content to match the interests of individual customers.

To sum up, AI has impacted social media marketing significantly. With further advancements in technology, AI will likely help companies enhance their social media marketing efforts in many other innovative ways. 

Conversation Intelligence using AI: The New Paradigm of Sales Enablement

Conversation intelligence transcribes and examines cold calls to accurately understand prospects’ priorities and needs – using their own words. 

First, the sales tool uses AI and ML to assess and convert rich first-party data (written or spoken) to deduce customers’ intent and sentiments. Then, it leverages NLP to tease out actionable insights from the conversations. 

As such, sales teams get the entire picture of all the conversations and take further actions in real time.

Conversation intelligence helps sales professionals learn what exactly is happening during a sales call. It surfaces the right insights at the right time. 

Among other advanced features, its call recording option offers a digestible view of the interaction and also allows for transcription so sales reps can focus on the conversation instead of taking notes. 

Case in point, conversation intelligence solution highlights the words or phrases that could hamper a deal.

Moreover, it evaluates the tones and emotions of both speakers, offering prompts in real time that aid the reps in realigning their ongoing conversation, avoiding basic mistakes, and closing more deals.

Based on these insights, businesses can ensure that no action items slip through the net during the sales call and after.

Recommended Read: Sales Automation: A Complete Guide for Sales Teams

JustCall IQ: A Super Brain for Sales Teams

JustCall IQ is a powerful conversation intelligence solution that gives you a clear picture of your pipeline and supercharges sales strategies.

Built for sales teams, JustCall IQ assesses every customer-facing conversation in real time and offers critical data points. The insights help examine KPIs and agents’ performance. 

Among other things, the solution identifies the calls that require urgent attention by discovering red flags such as competitor mentions, client objections, or compliance loopholes.

That way, sales reps can win more deals and boost customer satisfaction scores. 

With JustCall IQ, sales leaders can kick-start targeted sales coaching, learn what training programs drive positive change, and replicate what “sales rockstars” do best. Its core features include:

  • Real-Time Transcript
  • AI Scoring
  • Moment Analysis
  • Sentiment Analysis
  • Coaching Insights
  • Live Agent Assist

In all, the JustCall IQ conversation intelligence tool empowers salespeople to make decisions based on data instead of random opinions.

Learn more about JustCall IQ Pricing here

Justcall iQ - Conversation intelligence Pricing

The Verdict

The value proposition of AI-based sales assistants is indisputable. When it comes to the potential and possible disruptions of AI in sales and marketing, there are myriads of opinions out there.

“The great thing about AI is that it can predict and learn in real-time what the audience is going to be receptive to…[so we can] create a great value exchange between the brand and consumer in ways we weren’t able to do before.” – Bob Lord, Senior Vice President, IBM.

The world at large, and the sales realm, are sailing through similar paths – both looking for greater transparency, trust, and, eventually, truth.

Hence, sales executives are turning to data-enabled AI sales platforms to improve sales implementation and improve the odds of closing new deals.

If you aren’t already leveraging AI for sales, 2023 might just be the right year to make this happen.

Sign up for JustCall and supercharge your team to go from reps to #SuperReps. (Or schedule a free demo to learn from experts how JustCall IQ can be the growth driver for your business.)

Frequently Asked Questions 

How is AI used in sales?

AI software for sales help contact centers function and communicate with prospects more intelligently. Meaningful, actionable insights extracted from comprehensive data analyses help sales teams make correct decisions.

Further, the sales intelligence tool helps predict sales-ready leads, watch over agents’ performance, and optimize action items for better sales.

What is an AI sales assistant?

AI sales assistants are advanced computer programs that help sales teams scale by automating tedious recurring processes and tasks and identifying sales avenues.

Using NLP, ML, and speech recognition, these AI solutions help sales reps get inside the heads of potential customers, thus, empowering the former to create more customized pitches.

With this tech suite, salespeople can ensure effective, more relevant client-facing conversations that see favorable response rates.

How can artificial intelligence increase sales?

AI-enabled sales solutions recognize the prospects showing interest in purchasing a company’s products or services and determine the deal that will most likely resonate with them.

Also, their data-aware feature enables salespeople to spend more time on core activities, such as looking after existing customers and improving cold pitches, instead of doing repetitive jobs.

How does artificial intelligence improve customer experience?

Integrating AI with customer experience efforts helps support teams respond to customers in a more personalized way.

They can understand buyers’ intent, identify their past actions, even assess their sentiments, and tailor conversations accordingly. Making customer-facing interactions seamless and relevant improves customer satisfaction levels.

Is AI the future of customer service?

AI-based tools will make sales and customer support teams smarter rather than getting rid of them. The technology will free them from the low-value, tedious task of accumulating and evaluating massive data chunks from disparate systems.

However, contact centers still need human intuition to resolve complex issues of customers instead of repeating the same answers that chatbots and IVRs, which lack emotional intelligence, do.

As such, the future of customer service is human-machine synergy.

Will AI replace sales representatives?

The use of AI for sales and marketing will not replace human sales reps but the tasks they perform.

Moreover, not all sales jobs will get automated, but only those with recurring, low-level cognitive functions – data collection, segmenting leads, and more.

So, instead of wasting time on these menial tasks, salespeople will have a significantly crucial job – increasing customer lifetime value (CLV) and customer satisfaction (CSAT).

How to get started with AI in sales?

Sales executives need to focus on the following factors before jumping onto the AI bandwagon:

  • Identify the right business use case
  • Check sales data availability
  • Define the purpose, such as improved customer satisfaction, revenue growth, and salespeople performance
  • Create an actionable AI blueprint
  • Deploy suitable AI-based sales assistant bottom-up
  • Keep the system running with updated data

With a foundational role at Saas Labs, Anand has been a key player in establishing the Product Management function and spearheading the launch of our Conversation Intelligence solution. His expertise in AI innovation guides both the strategic direction of the products and a team committed to excellence.

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