Top Ten 7 Ways to Grow Sales from Social Media Using AI

Top Ten 7 Ways to Grow Sales from Social Media Using AI

The social media has evolved tremendously. What used to be just an online platform utilized mainly to share photos, play games, and connect with people has now become this amazing tool that companies use for sales and marketing. The social media, indeed, is a gold mine, and artificial intelligence has truly revolutionized sales. When you understand how it works and the rules of the game, the possibilities of growing your business are endless.

Let’s take a look at how people are capitalizing on social media and AI to scale their businesses.

Social Media Monitoring, Data Filtering, and Analytics

Social media platforms, such as Instagram and Twitter, have their own built-in analytics that look at the number of clicks, likes, and comments to gauge the success of posts. There are third-party tools, as well, that provide such analytics. These tools help determine the company’s audience by harnessing available demographic data, profile information, and consumer data.

AI can go as far as determining the most opportune time to post an ad, the probability of converting an impression, and the chances that your target users will respond to the ad that pops up in the middle of a video they are watching or an article they are reading.

This can give them an insight as to when to strategically post items to have an even wider reach.

Soon enough, companies might be able to rely on machine learning to identify which posts to place comments on, or which users to interact with to have higher sales success rates.

Image Recognition

Image Recognition

Image recognition features allow computers to recognize certain photos from posts even without accompanying labels, descriptions, or brands.

Whenever people post photos looking for recommendations or asking where they can buy the product and the image recognition software recognizes this, businesses can use this to send targeted promotions to that user.

Image recognition is also able to identify brands. When a user posts about a recent purchase of your products, this is a great opportunity to build customer loyalty when you comment or like the post. Furthermore, this may encourage the users to continue posting, making your products known in their circle.


Customers prefer a brand that they can connect with. The faster you can get to a potential buyer, the better your chances are at closing the sale. This is where chatbots come in. They emulate real conversations and are embedded in Facebook’s, Twitter’s, and Instagram’s messaging.

The more advanced chatbots are able to perform functions specific to the product or brand you are marketing. For example, Airbnb uses Amazon Alexa to greet guests and point them to popular local destinations. Estee Lauder uses a chatbot with facial recognition that identifies which shade works best for the user. Some chatbots have buttons for transactions or buttons that route users to the purchase page. Anytime the user is ready to purchase or place the reservation, he or she can conveniently click the button. Do not lose a customer who is ready to purchase simply because you do not have this feature in your chatbot.

Sentiment Analysis

Sentiment analysis evaluates the opinion of a text. This technology employs Natural Language Processing (NLP) with machine learning to match AI data and categorize texts as positive, negative, or neutral.

Companies use opinion mining or emotion AI to check conversations happening about the product and use these insights for their targeted promotions or interactions. If these emotion AI tools are able to spot a potential consumer contemplating a purchase, marketers can send these users promotions or a strategically-placed discount. It also helps them address issues, such as customer dissatisfaction.

Dynamic Product Pricing

Determining how much to charge your customers may take time and a certain level of expertise. Consumers, after all, look at pricing among other factors, so ensuring your product pricing is competitive is crucial. Thanks to advancement in machine learning, AI is now able to determine the best prices or the amount of discount needed to close the sale based on users’ data patterns. These dynamic pricing tools also have the capacity to measure the success of the price tips and adjusts the algorithm accordingly.

This is particularly helpful for companies like Airbnb. These pricing tools extract data – location, number of rooms, date of reservation, etc – and compare these to other listings that are getting booked often, factoring in seasonality. After getting the median from there, they then provide price tips.

Audience Targeting

Social media has become an effective platform to build brand image. With 3.2 billion active users, it is definitely a lot easier to get your brand across globally. With the use of social media, you don’t have to manually go to your consumers every time; rather, through effective marketing, with the use of artificial intelligence, you can bring the market straight to you, instead.

You can’t expect to bring all 3.2 billion to your brand. You wouldn’t want to, either, because not everyone is going to be interested. What we want to do is identify high potential consumers in the group. Companies save money and time when they are able to select and prioritize high potential prospects.

Prior to AI, companies have had to manually track data to identify their target audience. Even then, the results were not as accurate as those generated by machine learning, and the data was manually gathered retroactively.

AI can be trained to use the data initially mined by marketers and match them against a “gold standard” to draw out common properties and variables. They can, afterward, create these segmentations per gender, age, behavior, preferences, and buyer personas. Dynamic segmentation is also possible, as buying personas and customer behavior change from time to time.

Dynamic segmentation application uses real-time data to group buyers together in one segment based on buying behavior. This dynamic segmentation is then used by companies to send relevant offers. For example, if a consumer buying high-end headphones is identified, AI looks into his buying persona and behavior, performs the segmentation, and the company then sends that particular consumer relevant offers or discounts on high end headphones.

Content Optimization

Content Optimization

It’s hard not to notice how companies have stepped up their advertising and content creation game online. Social media posts need to be catchy and relevant and properly composed. Too much text makes your post look stuffy and boring. Textless posts may not seem insightful enough on the other hand. A balance of both is needed to pique your audience’s interest as well as keep them engaged.

A good sales company keeps its social media page regularly updated. Without diversification, the posts may come off boring and repetitive. We want our audience thoroughly engaged, so it is important to connect to them via relevant and interesting posts.

AI makes the job of getting the right combination of photos, text, and videos. Effective posts entice users to try your products and services, keep their membership, and stay loyal to your brand.

Artificial Intelligence and social media have definitely grown by leaps and bounds, and the sales landscape has changed. This gives startup companies a fair chance at success if they know how to leverage on this tech advancement. People are continually working on innovating or enhancing their current tools even further. Companies definitely have a lot to look forward to in the coming months.

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