What Is AI Marketing?

AI in Sales and Marketing: 2023 Statistics

Artificial intelligence (AI) is a fast-growing business that's appearing in more and more industries around the world. We've looked into how AI can be used in sales and marketing, including the benefits and potential risks that come with it.

Key findings

• The global AI market size is predicted to grow to $1,847.58 billion by 2030, while the chatbot market size is forecast to hit $1.25 billion USD in 2025.
• Customer service teams who used an AI-based conversational assistant saw a 14% increase in the number of issues they resolved per hour.
• 23% of marketing professionals use AI in their work, along with 21% of sales professionals.
• Companies saw a 50% increase in sales leads when incorporating AI tools in their sales process.
• Businesses could save an estimated $89.07 billion per year if salespeople used AI to complete data entry and non-sales related tasks which currently take up 70% of their time.
• Common risks of using AI that companies identified included cybersecurity (55%), regulatory compliance (36%), and personal privacy (28%).
• One-third (33%) of marketers said the top benefit of using AI and machine learning is how much time it saves.
• 89.6 million people in the US report that they interact with AI several times a day.

How can AI be used for sales and marketing?

There are countless ways companies can use AI for both sales and marketing. Some of the key advantages are increasing productivity, personalising customer experiences, and analysing data. But how exactly have companies, sales leaders, and marketing managers adopted AI technology to improve their business outcomes?

Examples of AI in sales

Sales teams have implemented AI into their processes in several ways, here are a few examples of AI working alongside sales technology.

Upselling and cross-selling

Amazon uses an algorithm to tailor item recommendations to customers based on what they have previously bought or searched for. This effectively gives every Amazon shopper their own personalised storefront with items that are more likely to be of interest to them, and therefore more likely to land Amazon a sale.

Freeing up more sales time

Salespeople can sometimes get bogged down with admin work and data entry which takes time away from sales-related tasks. Data shows that salespeople only spend around 30% of their time actually selling. AI can be used for mundane and repetitive tasks like logging sales team activities and recording data, freeing up more time to deal with customers and make sales. Using tools like call transcription software can save time on manual data entry, making logging information much more efficient.

There are over 2.3 million salespeople in the US, with a median salary of $55,328. This means companies pay salespeople an estimated total of $127.25 billion every year, but only 30% of their time is spent on sales. Therefore the remaining 70% of the time wasted amounts to $89.07 billion. This money could be saved or recouped in additional revenue if sales teams were able to use AI for CRM data entry tasks and dedicate 100% of their time to sales.

Sales forecasting

AI tools can be used to forecast sales by analysing historical data and predicting future results. It can help sales managers forecast their sales team's performance and even predict new sales prospects who might be interested in what you're selling. AI tools can analyse much larger amounts of data, allowing them to make more accurate predictions relating to sales performance.

Customer service chatbots

Businesses can use AI chatbots to communicate instantly with customers, answer questions, collect data, and recommend products. One example is fashion retailer H&M's chatbot which provides information on product availability, a customer's closest store, and other advice based on customer queries.

Examples of AI in marketing

AI tools can also be used in marketing strategies, like the examples below.

Providing a personalised customer experience

Studies show that 36% of consumers think businesses should try to offer more personalization when it comes to customer experiences.

Grocery chain Whole Foods opened a selection of ‘Just Walk Out' stores in the U.S. in which customers simply pick up their items and leave. The stores use Amazon's AI technology to monitor the items taken and then charge the customer the correct amount. A key benefit of AI tracking the items someone buys is that it can analyse each customer's shopping trends and predict future purchases.

Streamlining user experience

The latest reports show that 50% of the U.S. population uses voice search every day; this amounts to around 166 million people.

Coffee giant, Starbucks integrated Amazon Alexa technology into their ‘My Starbucks Barista' service. This allows customers to place orders, amend them, and confirm collection locations using voice commands and chatbot technology through their smartphones.

Content creation

Artificial intelligence tools are capable of writing original content like blog posts, emails and product descriptions, as well as editing human-written copy. This can save content writers time and allow them to increase their output.

One example of such a tool is Copy.ai which can write sales copy, social media posts, emails and more. It also enables you to provide clear context for the content you want it to create, giving the finished content a more human-like feel.

Data shows that 65% of content marketers plan to use AI content generation tools to write copy.

Machine learning sales examples

When it comes to sales functions, machine learning can be used to understand and predict customer behavior, improve decisions, and increase sales performance and productivity. Using machine learning in the sales process enables sales leaders to determine things like:

• Which customers might respond positively to a particular product or service
  
• What kind of products certain groups of customers are looking for 
• How long it will take to convert a sale

Here are some real-world examples of machine learning being used in sales:

• Sephora uses a machine learning application which enables customers to upload a photo of themselves and try out different products and makeup shades on themselves before they buy.
  
• The North Face uses AI and machine learning in the form of the ‘IBM Waston’ tool which acts as a virtual salesperson on their website, asking customers questions in order to recommend products that will suit their needs.

Machine learning marketing examples

In marketing, a machine learning model can be used to create customised marketing campaigns that are targeted at individual customers. These models can also identify patterns in large datasets which could be used to inform future campaigns.

• Netflix uses machine learning to predict which shows or films users will want to watch next based on their previous viewing behavior.
  
• Spotify predicts when customers might be thinking of leaving their service by analysing user behavior and other data to predict these patterns. They will then provide incentives like discounts for the customer to stay.

Statistics on AI in sales and marketing

Let's take a look at some interesting statistics from the latest reports on AI in sales and marketing.

AI market size

The global AI software market's market size was $95.6 billion USD in 2021. It is predicted to grow to $1,847.58 billion USD by 2030. This would be a 1,147% increase over that seven-year period.

How many people are using AI?

In the US, over a quarter (27%) of people say they interact with artificial intelligence several times a day; that's around 89.6 million people. An additional 28% say they interact with AI several times a week, while 44% report that they use it less often than this.

Data shows that people working in marketing and sales teams are among AI's top 10 user groups. Just under a quarter (23%) of marketing professionals said they use AI at work, along with 21% of sales professionals. The top users of AI are IT professionals (51%) and data engineers (35%).

Of companies who had implemented AI into their processes, 26% said they were using it for sales and marketing-related tasks.

How many companies use chatbot software?

Statistics show that B2B companies are more likely to use chatbots, with 58% saying they use them regularly, compared to 42% of B2C companies.

The online chatbot market is forecast to hit $1.25 billion USD in 2025, a 555% increase from its value of $190.8 million USD in 2016.

Other reports state that the global online chatbot market was worth $0.84 billion USD in 2022 and is predicted to reach $4.9 billion USD by 2032.

The use of natural language processing

Natural language processing (NLP) is a type of AI that can understand and respond to text or voice data in a very similar way to humans. This technology can also be used for sales enablement processes like taking call transcripts, analysing conversations and providing statistics and recommendations.

Although this technology has many uses, including in sales enablement, the most common application for NLP tools is in customer care with 38% of businesses using them for this purpose, but 30% of companies also said they use NLP for sales processes, and 29% use it for marketing.

In 2022, the Global NLP Market was $15.7 billion USD, and is predicted to grow to $144.9 billion USD by 2032. This is a Compound Annual Growth Rate (CAGR) of 25.1%. The increase in demand for chatbots, virtual assistants and sentiment analysis tools is contributing to major growth in the NLP market.

What marketers find useful about AI

There are several ways that AI can help marketers generate results and improve how they analyse data.

One survey found that the top benefit marketers mentioned for using AI and machine learning (ML) was how much time it saves, with 33% of respondents citing this benefit. This was followed by the benefits seen in their insights and data on audience preferences with 31% of marketers saying they valued this improvement as a result of using AI and ML.

Just over a quarter (26%) of marketing professionals said that using AI technology and machine learning tools helped them to improve or optimise the content they were creating.

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How does AI increase productivity?

As we mentioned, one of the key benefits of using AI is that it saves time and allows workers to focus more on skilled work and less on mundane admin or data entry tasks. But just how much can artificial intelligence increase productivity in the workplace?

One study from the National Bureau of Economic Research analysed data from over 5,000 customer support agents. It found that when workers used an AI-based conversational assistant, the number of issues they resolved per hour increased by 14%.

The findings also showed that using the AI tool had the biggest impact on lower-skilled workers with less experience who were able to complete their work 35% faster. Using the AI assistant had a minimal impact on highly skilled, experienced workers.

The authors of the study concluded that assistance from AI improved employee retention, created better customer sentiment, and reduced requests for support from managers.

Does using AI increase sales?

A study from Harvard Business Review found that using AI has a number of effects on the sales that a company can generate. It found that:

• Companies that used AI tools when making sales increased lead generation by 50%.
• Call times by sales reps using AI were reduced by up to 70%.
• Companies saw a reduction in overall costs by up to 60% when they implemented AI technologies into their sales process.

In addition to this, the share of companies who report that at least 5% of their earnings before interest and tax (EBIT) can be attributed to AI is 27%, an increase from 22% in the previous year.

Barriers to AI adoption in sales and marketing

While AI has plenty of benefits in the sales and marketing space, there can also be challenges associated with implementing these tools into marketing and sales teams.

Companies that had not adopted AI cited a number of things that were hindering them from doing so. The top reason was that they had limited skills, expertise or knowledge in AI, with 34% of companies saying this was stopping them from implementing AI tools. Other barriers included AI being too expensive (29%), and companies lacking the tools needed to develop models and test the effects of AI.

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This data suggests that some companies are still not in a position to adopt AI and will need time to invest in education and tools in order to implement it.

A survey of marketing professionals found that 45% of them said they are beginners when it comes to using AI for marketing. Almost two-thirds (63%) said that a lack of training was a barrier to them adopting AI for marketing, and only 11% said their company provided formal AI education.

Risks companies identified with using AI

For companies who have begun using AI, there can be risks involved which need attention to ensure potential harm is avoided.

Organizations that had implemented at least one function of AI were asked which risks they thought were relevant and were working to mitigate. The most common risk identified was cybersecurity, with 55% of organizations saying this was a potential challenge they were dealing with when using AI. This was followed by regulatory compliance (36%) and personal privacy (28%).

Other risks included the organization's reputation (22%), equity and fairness (17%), and in some cases even national security (7%) and political stability (4%).

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The future of AI in sales and marketing

We know that AI offers a number of benefits in the world of sales and marketing in terms of productivity and customer engagement. But there are still barriers that make it difficult for some companies to adopt this technology.

When it comes to sales, call centres use many types of software, and AI is found more often in these settings. The market size of call centre AI is predicted to grow from $1.6 billion USD in 2022 to $4.1 billion USD in 2027, with a CAGR of 21.3% during this period. This shows the potential that AI has to transform the way businesses create sales strategies by automating processes and improving productivity.

Will AI replace sales and marketing jobs?

There is a lot of talk about AI replacing humans in the workforce, with economists from Goldman Sachs reporting that AI could replace up to a quarter of current jobs globally (that's around 300 million jobs).

But can AI really replace sales and marketing professionals? It's unlikely that AI will replace these roles completely as there are limits to what AI tools can do and how they can interact on a human-like level.

It's expected that AI-powered technology will become a digital assistant for every member of a sales team, allowing them to increase productivity by up to 50% and spend more time on sales-related tasks. While it's true that AI is making significant advancements in how businesses carry out sales and marketing, human knowledge and experience are still needed to manage complex processes and customer interactions.