Retailers must understand and harness the power of ambient data, now, writes Cameron Curtis.

The mantra of the retail sector has always been location, location, location. But lately, with the explosive emergence of big data, data science, internet of things (IoT), machine learning, artificial intelligence, and wearable technologies a new punch line has emerged: data data data. Data is the new currency that brands and organisations all over the world are now trading with. So, what happens when you marry location and data? You end up with a hybrid power: ambient data.

What is ambient data, and how can retail businesses harness this new superpower?

Ambient data explained

After the immense popularity of smartphones, the latest in technology boasts a new generation of smart interconnected devices (IoT sensors). When you connect these smartphones and smart devices with the powerful and ubiquitous cloud technology, “smart environments” are born. These smart devices, as Microsoft’s CEO Satya Nadella says, “have the capacity to listen to us, respond to us, understand us, and act on our behalf.”

In simpler term, these environments are extremely sensitive and responsive to human events, and can over a period of time learn and adapt to users’ needs and behaviours. This is known as ambient intelligence, which allows us to accurately map an individual consumer’s journey not only in the digital world but also in the physical world, providing us rich and deep insights into user preferences and behaviours.

Ambient data is generated from connected environments that help map the physical world. Until recently there was no way for businesses to take advantage of this data. In the digital world, many ecommerce sites track their customers’ digital footprint and then send emails regarding the particular item when it’s on a promotion; it was very hard to do something similar in the physical world. Ambient data changes this by enabling organisations to quantify and measure the physical world, and take action.

An example

The popular example is that of a smart home. You return home after a tiring day at work. The intelligent surveillance camera at the front door recognises you and turns off the alarm to let you in. Once inside, the alarm is reactivated. Now that you are inside your home, lights come on and the curtains open automatically in the rooms you go in and switch off when you leave them. Next, you enter the kitchen and your refrigerator tells you the supplies that you are low on. Once you confirm or make changes, the shopping list is automatically sent to the connected supermarket for delivery. When you switch on the TV, you land at your favourite channel (instead of having to browse to it). Your Smart TV having learnt the channels you watch most frequently, navigates through them first instead of going sequentially.

When you extrapolate this scenario to the next bigger scale, you get smart cities. Traffic signals that assess the traffic situation and intelligently regulate the traffic after “conferring” with other connected signals. Water plants that automatically monitor the situation and regulate the water flow based on demand or natural conditions.

So, how will my business benefit from this ambient intelligence?

We can best understand this with the help of some use cases.

Case 1: Maximising sales of home loans

Suppose you are a branch of a banking organisation. You want to maximise your home loans sales. In this case, you first “feed” the locations of the housing projects in your portfolio into the the ambient intelligence platform and then you monitor the activity during inspection hours and viewing hours to understand the preferences, behaviours, and demographics of customers. Once you have gathered sufficient data, such as the average pricing of the houses, the range of disposable income of the customers, their existing home locations, you can then use this dataset to tweak offers for home loans to make them more enticing to the group of potential homeowners depending on their budget.

Case 2: Competitor intelligence for product pricing

You want to specifically monitor the consumers that visit the retail stores of your competitors and redirect them to your stores. You can do so by monitoring the locations of your competitors’ retail stores and display targeted messages to all people who are within the 200-meters range of the store. You can then also track how many of these people actually visited your nearby store. Similarly, you can monitor what the people visiting your competitors’ stores are looking at, what they are buying, and what they are not, to tweak your own prices and offerings. You can also get insight into how far the consumers of your category travel to shop, and make decisions on home-delivery options to get a competitive edge.

Case 3: Contextual marketing based on real-time data

You are a up-and-coming coffee brand in a new region that wants to reach consumers within half a mile radius of your every individual store and drive footfall. You can do so by monitoring weather conditions as well as locations of your stores. For example, if the weather is hot, you can target potential customers in the vicinity of a store by displaying ad for your range of cold coffees, while in case of chilly weather, you can send targeted ads extolling your range of hot coffees. Surge pricing for products can also be explored using this intelligence.

Case 4: Bringing measurement to traditional media

Suppose you want to advertise for an upcoming sale using billboards. But you know that renting billboard space is expensive. So to justify the high cost and get maximum ROI, you want to identify the strategic locations where your billboards will have maximum impact and drive footfall to your retail stores. So, the problem here is how to measure the effectiveness of your advertisement. In this case, you can track the footfall in the vicinity of the planned locations, and then understand the behaviours and preferences of the passersby who will be potentially exposed to the billboard. You can even track where they go after they see the billboard.

In Summary

When used efficiently, ambient data can give you deep and real-time insights and predictive analytics about products. For example, by tracking what product was picked up by a store visitor in your or a competitor’s store and knowing for how long they held it, you can gauge their true interest in the product. This can help you optimise how the product is placed, where it is placed in the store, and what can be its optimal price to give you that edge over your competitors.

Similarly, ambient data also gives you a deep understanding of the preferences, behaviours, location, and the ambience of your potential customers. When used correctly, this actionable information can be translated into compelling benefits and opportunities for brands and organisations.

The importance of ambient intelligence can be succinctly summarised with a quote from Satya Nadella, CEO of Microsoft: “The era of ambient intelligence has begun…..”

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Cameron Curtis is the general manager, Australia and New Zealand of Near.

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Image copyright: 123RF/  Sergei Tiden