Artificial intelligence helps companies detect buying signals from customers or website visitors by analysing and interpreting data. Let’s see how small businesses can benefit from using AI to identify the intent of purchase.

In today’s highly digitized world, small business owners need to facilitate regular and instant communication with their target customers to increase engagement and brand awareness.

Predictive intelligence, more commonly known as predictive analytics, is a subset of AI that comprises an array of statistical models that analyse historical and current data on customers' behaviour to study various stages of their purchase journey.


For example: if someone is looking to purchase a new smartphone and searches for smartphones on a search engine such as Google. The search action performed by the customer is called a ‘trigger event’ of which smartphone brands and sellers get automatically notified.

The specific search action presents an excellent opportunity for the latter to provide prospective customers with suitable suggestions on various smartphones.

Furthermore, let us say that the customer is a traveler who is always on-the-go. AI-based predictive analytic models can analyse this information and suggest those smartphones that are travel-friendly and have a longer battery back-up.

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Two sides of the same coin

Having said that, predictive analytic models achieve the same by breaking down data into two categories: internal data and external data.

A company’s internal customer data includes buying cycles, purchase patterns, firmographics, sales data, purchase histories, and so on.

External data is what is available outside of the company’s records. That includes publicly available information such as the buyer persona, marketing campaigns, FAQs and their social media activities.

Here’s an example of the types of customer data and from where it can be collected:

The different types of customer data and where can you obtain them from.


Third-party information sources can also be an added advantage to the sales teams in the company because they provide a comprehensive view of the prospective customer.

Now that you understand the basics of predictive analysis, let us dive deep into how the AI-empowered technology can help your small business identify the intent of purchase:

1. Purchase history analysis

As discussed earlier, predictive analytics analyses the purchase history of a large set of customers to predict future buys, or to provide suggestions such as the best time to have a sale, which seasons to target, what products to recommend, and so on.

For example, consumers in Europe and America are inclined to make more purchases during festive seasons such as Christmas and New Year’s. By analysing the surge in buying patterns around these dates, the model can predict that a sale during this time will fetch better results.

The information thus enables small business owners to design customised marketing campaigns for maximising sales in the holiday season.

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2. Sentiment analysis

Sentiment analysis tools use machine learning and predictive analytics to scan through large volumes of data and compile that data to identify the tone and emotions in the target customers’ social media interactions that could be positive, neutral, and negative.

These interactions include their comments on social media, customer reviews on your website or online forums, or mere engagement with your brand on mobile. The main goal of sentiment analysis is to understand whether your business is engaging the target audience.

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3. Social media analytics

The most effective platform where small business owners can put their predictive analytics tools to the test is on social media. Because social media sees the maximum engagement from both consumers and the brands, it also has an impact on marketing and sales.

Predictive analysis can be used for social media, through Datoin.


Consumer interactions on social media, including likes, comments, follows, shares, and reposts, are analysed to know how small business owners can focus their marketing and sales efforts for a specifically targeted audience.

Besides, sentiment and text analysis tools tell you how prospective customers are reacting to your posts or the content you share on your social media page. It allows you to make changes accordingly and increase your chances of engaging with them positively.

Thus, using this information, predictive analytics draw insights and enable you to streamline your marketing processes and sales strategies following proper targeting and segmentation of your target audience.

4. News analysis

Businesses today, irrespective of sector or size, want to keep their customers involved and informed at all times. That’s why most of them publicly make announcements about recent purchases, business mergers and acquisitions, newly formed client partnerships, and more.

It’s their way of involving their customer base within the happenings of the business and also attracts potential buyers, investors, and vendors.

Therefore, the ‘news-related’ data can be effectively used by small businesses to design marketing and sales campaigns that target a broader audience.

Keeping track of the data also enables them to segment their prospects accordingly so that they can be specifically targeted for a particular product or service. That is an effective technique to increase brand engagement and improve conversion rates.

Over to you

The contribution of AI and its subsets such as predictive intelligence can’t be ignored by small businesses, given how the technology helps them make their sales efforts more effective. Moreover, an AI-driven sales strategy can streamline the marketing process of your business and enable to-the-point targeting and segmentation.

At the end of the day, if you know who your customers are, what they are looking for, and when they want to shop, it will be a lot easier for you to drive sales and boost revenues.

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