The arrival of artificial intelligence (AI) in tools makes marketing and sales departments more productive, effective and saves on costs. The tools support the creation of content, lead generation & follow-up and communication throughout the entire process.
You probably recognize the following situation: when you watch a series at Netflix, similar series are automatically presented. You might also find those series interesting because of similarities such as genre or actor. A week later you will receive an email in the afternoon reminding you of these series. The incentives encourage you to watch them that same evening.
Artificial intelligence (AI) is applied using computer systems and algorithms to simulate human problems, solutions and choices as accurately as possible. The system tries to match a human level of intelligence but in a much shorter time. AI marketing offers the possibility to analyze the activities of leads and customers. Subsequently, we act predictively and look for engagement with potential customers (for example with e-mails).
Content developed by AI
The data-driven approach is already being actively used for consumers. It is also being used more often in B2B. Although much is automated within marketing, human actions remain necessary. For example, when creating content. But there too we are already seeing many developments to create (data-driven) content on a larger scale.
An example is the Content Strategy tool from HubSpot, which helps the marketer to gain insight into the most important themes for the target group. The content to be written is not only focused on a set of keywords but written on a theme and associated sub-themes. This way the creation of content is tackled more efficiently and smarter.
On a larger scale, you can even think of writing product descriptions with the help of Natural Language Generation (NLG). NLG converts structured data into readable text with the help of predefined rules and frameworks. An SEO-friendly description is automatically generated with elements such as type, color, dimensions, model and price. Writing 10,000 unique product descriptions is suddenly possible with, for example, the use of Wordsmith.
However, we are not yet ready for machines to produce a substantive piece of text of a thousand words about Enschede, which also benefits the reader.
Effective lead selection and follow-up
Business-to-business organizations have many opportunities so that sales can select and follow up leads more efficiently and effectively. With the use of artificial intelligence, for example, important similarities are found between specific customers and groups. Points are awarded to these agreements, to then apply these agreements to the group of leads. These leads receive a lead score based on the agreements. This form of predictive lead scoring works very well if you have many leads and a heavy sales force. After all, it offers you the opportunity to follow the best leads first. Leads where the best chance of success lies and the lifetime value is the highest.
Think about following up on a personalized and personalized scale. Only the selection is already time-consuming. If you also want to approach the leads in a personalized way, it will take even longer.
AI marketing allows you to send your leads an e-mail based on historical interactions. That way you automatically increase engagement with your brand. Where you used to send a mailing by default in the morning, the system predicts on the basis of AI when the chance is greatest that the recipient will open the e-mail and take action.
Anxiety or adaptation?
It is important to know that the role of AI is not to eliminate tasks, but rather to eliminate, automate or at least change tasks that are time-consuming. As a marketer or sales, we can concentrate on activities that are most valuable at the bottom of the line. As an organization, we should not be afraid to embrace technology and see its benefits.
The use of artificial intelligence is unfortunately not just for every organization. Even if you want to adopt AI: you need data, time and resources to set up the systems and to continuously manage and make them self-learning.
Think about which tasks within your organization cost a lot of time and are data-driven. There may also be opportunities within your organization to streamline sales and marketing activities with the use of AI systems and tools.