Indoor Mapping And Machine Learning: The Key To Future Retailer Success

Posted by Noah Oliver on June 7th, 2019

In the current industry scenario, machine learning and indoor mapping are two tools that every business wants to approach, thanks to their potential to improve the user experience while multiplying sales. The solutions of machine learning and location intelligence have combinedly bought other solutions such as indoor mapping. Indoor mapping, despite being in the development stage, has already proven to be highly efficient in making the best decisions and increasing the prospects of better results. Indoor mapping can be determined as a sub-section of location intelligence, but the only difference is that the location takes place on the inside.

In this post, we will discuss how machine learning and indoor mapping can serve your business together, especially in helping you increase your sales volume.

What is indoor mapping?

Marketing can use location intelligence to improving customer understanding. The multiplying of localized devices like smartphones, vehicles, and even wearables, makes it easier to track the customer’s location.

This is where indoor mapping comes into the play. If applied correctly, it can be extremely beneficial. Through indoor mapping, you can map and learn where your consumers move inside the indoor space, dwell times, where they stand. And depending on what is not bought and what is bought, this can give you an insight into how long it takes for a customer to make a buying decision. Some of the significant benefits of indoor mapping include:

• Faster calculated routes between two points
• Locations of hot spots for sales
• Improved user experience
• Improved line management

Indoor mapping is still a nascent technology and thus requires a combination of multiple indoor geolocation systems for producing optimum results.

What is machine learning?

Machine learning, as the name implies, enables the machine to learn from the information it collected. The more the data is analyzed; the lower will be the percentage of error. Machine learning is all about predicting the future trends and behavior, in addition to rapid processing of data. Solutions based on machine learning, hence, is critical for a business’ growth in today’s time. Companies such as Amazon use machine learning that allows them to learn about their users from all the interactions continually. 

All these interactions at high speed, low cost, the minimum margin for error, and dynamization of data are some of the factors that roots for this mechanism’s efficiency. Through machine learning, companies can generate large amounts of data, which can be used to tackle real-time problems and create more sales.

So, how do machine learning and indoor mapping fit together?

When machine learning and indoor mapping are combined, it ultimately increases the commercial advantages. In simple words, you get to have all the data cataloged, geolocated, and processed in real time. On the other hand, quality and control about the decision-making process become even more significant. This enables you to increase your profits while offering better services. In addition to that, you can also provide your customers with a personalized service with non-invasive strategies, and that too in real time.