AI for marketing and sales

Both marketing and sales are directly responsible for generating revenue. This unique position gives the two functions significantly more power to direct investment into new projects. The need to keep up with competitors in fighting for market share means that both units are, on average, much more willing to try new tools as well, including the latest technology advances based on artificial intelligence (AI).

We’ve covered AI applications in marketing and sales extensively here at TOPBOTS, including:

Generative AI has opened up new ways for AI to boost marketing and sales effectiveness and efficiency. AI can now assist with consumer research to build branding strategies, create engaging textual and visual content, personalize content for each potential customer, and understand how consumers will weigh your message against those of your competitors.

In this article, we will review what predictive AI and generative AI have to offer to boost sales, and how AI is revolutionizing product marketing and sales by making new things possible, more efficient, and simply better.

Predictive AI and Generative AI in Marketing & Sales

In our earlier article, we discussed how predictive AI is used to predict future events, while generative AI is a type of AI that creates new content.

In the context of marketing and sales, predictive AI analyzes historical data to forecast future trends, customer behaviors, and marketing outcomes. It’s about anticipating the next move in the market or consumer behavior based on past patterns.

Let’s say a clothing retailer wants to segment its customers into different groups based on their purchase behavior. They use a predictive AI model to analyze their customer data, including demographics, purchase history, and website browsing behavior. The model identifies four different customer segments:

  • Fashionistas: These customers are interested in the latest fashion trends and are willing to spend money on new clothes.
  • Budget-conscious shoppers: These customers are more price-sensitive and are looking for good deals.
  • Basics buyers: These customers are primarily interested in basic clothing items that are comfortable and affordable.
  • Occasional shoppers: These customers only shop for clothes occasionally, and they are typically looking for specific items.

The retailer uses this information to create more targeted marketing campaigns for each customer segment. For example, they might send fashionistas email newsletters about new arrivals, offer budget-conscious shoppers discounts on sale items, and target basics buyers with ads for essential clothing items.

On the flip side, generative AI is about creating new data resembling the original data set. It’s not about forecasting, but generating new content that resonates with target audiences.

The clothing retailer from the previous example can use generative AI to create personalized ad campaigns for the different customer segments they have identified. They could leverage LLM-based applications and image-generation software to generate personalized email newsletters, targeted social media ads, and dynamic website content.

For example, when targeting the segment of basic buyers, generative AI can be used to create personalized ad copy that highlights essential clothing items and timeless styles, like “Shop our selection of basic clothing items for men and women, at affordable prices.” The AI could also generate personalized product recommendations based on the basics buyer’s past purchase history. For example, if the buyer has recently purchased a pair of black pants, the AI could recommend other basic items, such as a white button-down shirt or a black blazer.

By using generative AI to create personalized ad campaigns, the retailer can increase the relevance and engagement of its marketing messages, which leads to higher click-through rates, conversion rates, and customer satisfaction.

Re-Defining Marketing & Sales

AI is transforming the marketing and sales landscape, making new things possible, increasing efficiency, and boosting performance.

ai for marketing and sales

Firstly, it pioneers new possibilities by unlocking capabilities that were once deemed impossible:

  • Hyper-Personalized Content Creation: Generative AI enables the automatic generation of highly personalized content, such as tailored advertisements, personalized emails, or unique landing pages based on individual user behavior and preferences.
  • Real-Time Customer Behavior Analysis: AI is able to analyze customer behavior in real-time to offer personalized recommendations or content, enhancing the customer’s interaction with the brand.
  • Virtual Sales Assistants: AI-powered virtual assistants can handle customer inquiries round the clock, providing instant responses and guidance which wasn’t possible with human-only sales teams.

Next, AI significantly trims operational costs and time expenditures by automating several routine yet crucial tasks:

  • Automated Lead Scoring: AI can automate the process of lead scoring by analyzing multiple data points, making the sales funnel more efficient and reducing the manual workload.
  • Optimized Advertising Placement: AI can determine the optimal platforms and times for advertising to ensure maximum reach and engagement, reducing wastage of advertising budget​.
  • Sophisticated Sentiment Analysis: AI-powered algorithms, including LLM-based solutions, can automate the analysis of customer feedback and identify sentiment in great detail, including all the different aspects, such as sentiment towards specific topics (e.g., price, features, customer support), emotional tone, and intentions.

Lastly, the essence of AI in enhancing performance cannot be overstated:

  • Dynamic Audience Segmentation and Targeting: Generative AI can dynamically segment audiences and create personalized outreach content at a scale that was not achievable before, identifying new audience segments based on large sets of data​.
  • Enhanced Customer Relationship Management (CRM): AI can analyze customer data to provide insights, helping sales teams better understand customer needs and preferences, which in turn improves relationship management and sales performance.
  • Comprehensive Sales Data Analysis: AI can be used to analyze sales data more effectively than ever before. This can help businesses to identify trends, opportunities, and areas for improvement.

These are just a few examples of how AI is revolutionizing marketing and sales by introducing new possibilities and improving existing practices. The next big question is how to bring AI into your marketing and sales activities.

Implementing AI-Powered Solutions

Companies can introduce AI into their marketing and sales solutions in several ways.

  1. Building AI solutions from scratch gives companies the most control, but it is the most expensive and time-consuming option. This path is usually chosen by large companies with sufficient resources and specific needs that cannot be met by existing solutions.
  2. Using off-the-shelf AI solutions is a more common option. Tech leaders and AI-focused startups offer a variety of ready-to-go solutions that can help businesses automate tasks, personalize the customer experience, and gain insights into customer behavior. For example, IBM Watson Advertising offers solutions for anticipating consumer behavior, delivering ads strategically, and creating effective ad campaigns. Then, there are smaller specialized AI companies that, among other things, can assist businesses with:
  1. Partnering with AI companies to develop custom AI solutions for marketing and sales is another option that can be good for companies that want more control over their solutions or have specific needs that cannot be met by off-the-shelf solutions.

Every business can find a way to successfully bring AI into their marketing and sales activities and reap the benefits of this powerful technology.