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What are the best AI-driven demand generation strategies?

Generating quality leads and converting them into customers is today’s major business problem. What are the best AI-driven demand generation strategies? There are, by the way, no shortage of possible answers to this question. Demand generation is about creating demand for your product or service. It’s largely a marketing function, and it has a lot of processes and a lot of people associated with it. From the perspective of using AI to improve demand generation, we should be looking mainly at two areas: outreach and the processes associated with it, and demand generation itself, which generally involves people marketing to people.

Understanding AI in Demand Generation

Prior to delving into distinct tactics, it is fundamental to grasp what AI can accomplish in the realm of demand generation. Artificial intelligence dissects enormous quantities of data to spotlight patterns, foresee results, and streamline operations. Using AI, teams can customize their marketing and supercharge their decision-making.

Per a report from McKinsey, businesses that are using AI for marketing are seeing a 10-15% lift in revenue. In addition, AI tools can help firms save up to 30% on their marketing costs by optimizing campaigns in real-time. So, if you’re not using AI for demand generation yet, you’re at a serious disadvantage in the current competitive landscape.

What are the best AI-driven demand generation strategies?

Let us now comprehend the function undertaken by artificial intelligence and then explore the most effective strategies that businesses can embrace:

Analytics Used for Prediction: This approach involves the examination of data derived from the past to conjecture about what might happen in the future. By “guesstimating” in a scientific manner, businesses can ascertain with a fair amount of accuracy which leads are more likely to convert. Working with those leads, businesses have reported upwards of a 20% increase in conversions.
Individualization: AI enables companies to furnish individual content to prospective customers. By fine-tuning messages to the nuanced behavior and predilections of users, companies can take customer engagement to a new level. Epsilon carried out a study that discovered 80% of consumers are more inclined to make a purchase when provided with individual experiences.
Chatbots and Virtual Assistants: AI chatbots can hold conversations with visitors on business websites, respond to their questions, and even figure out what kind of leads they are. Dialogflow tells us that using their platform, which is Web-based and works with Google Cloud, Drift was able to push its lead generation up 5-10%.
Lead scoring that is done automatically: AI can assist in ranking leads based on their probability of conversion. When leads are scored automatically, the sales process is streamlined, and high-potential leads receive high-touch treatment.

Enhancing Content Strategy with AI

Demand generation relies heavily on content marketing. AI can take content strategies to the next level by parsing huge amounts of data and figuring out what really speaks to the target audience.

With tools such as Grammarly and Clearscope, marketers can effectively optimize their content for both SEO and engagement. Moreover, AI algorithms can now do much of the heavy lifting in suggesting topics based on trending searches. In this way, content creators are guided to produce even more relevant material. When this “relevant by AI” content is aligned with audience interests, its potential for traffic and engagement increases. In turn, this traffic and engagement contributes to the overall success of demand generation.

Leveraging Data for Targeted Campaigns

One of the most attractive aspects of demand generation driven by AI is the opportunity to use big data for finely tuned campaigns. AI can take the vast amounts of data we have about our customers and potential customers and find meaning in it. We can then use the insights that come from AI to build much smarter, tighter demand generation machines.

As an example, HubSpot is a company that uses artificial intelligence to the fullest. They utilize it in a few different ways, one of which is segmenting their customers into different buckets so that they can send out emails that are more relevant to the people receiving them. This is something that not just HubSpot does, but a lot of companies in the marketing technology world do, because it is kind of a cornerstone thing that artificial intelligence allows you to do—make more segments and better segments.

Measuring Success with AI Tools

Ensuring the effectiveness of these AI-based strategies necessitates knowing their return on investment. For this, a variety of AI tools can be harnessed. They help businesses measure and make sense of the signals coming from the demand generation part of the funnel. Two tools commonly used for this purpose are Google Analytics and HubSpot. Both provide a wealth of information about the performance of the campaign and the kinds of customers it is engaging. Both also track sales conversions.

Monitoring the success of campaigns allows for the adjustment of business strategies based on current data—right down to the minute. This real-time feedback lets companies pinpoint where to direct their resources and where to invest in tactics that, thankfully, seem to be working.

The Future of AI in Demand Generation

Demand generation’s role is changing rapidly due to the advancements in technology, and we must remain current on the new trends that are coming our way. Today’s strategies revolve around automation, personalization, and integration. Tomorrow’s strategies will focus on the same three key components, but with AI, demand generation will evolve even further.

Organizations can continue to meet the demands of their customers and can remain competitive if they adapt to continual change. It is, of course, not enough to know just any old thing about AI-driven demand generation. Businesses must have a deep understanding of the best strategies that artificial intelligence has yet driven.

Conclusion

In summary, demand generation strategies that use AI give businesses something they need when trying to enhance their marketing efforts: a better way to predict the future. For what is content marketing (or tomorrow’s equivalent) if not a way to populate the sales funnel with prospects whose next moves can be anticipated? And in that context, better content isn’t just different content; it also isn’t just better-written content or better-designed content. It is more engaging, yes. But above all, it is more “understandable,” by which I mean it is “understandable” in the way that good anticipatory content should be.