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Understanding behavioural analytics with Near’s Allspark
August 5, 2019 News


Near is the world’s largest source of intelligence on people and places, processing data from over 1.6 billion monthly users across 44 countries. Using AI to make real-world data actionable, the platform has the largest data-set of people’s behaviour in the real world. Brands, enterprises and publishers leverage the use of location, transaction and other unique real-world signals from over 1.6 billion users in the platform for data enrichment and marketing, in a privacy-led environment.

Its flagship Software-as-a-Service (SaaS) product, Allspark is the first of its kind in the industry. It enables end-to-end marketing automation for clients and partners across over 20 countries. With its seamless usage, users use their first-party data, and real-world data to deliver superior customer experiences.

Disruptive Tech Asean spoke to Shobhit Shukla, Co-founder and Chief Revenue Officer at Near to get his insights on this consumer behaviour analysis platform. Shobhit explained that the growing number of connected devices in the world would lead to data deluge and deriving relevant behaviour analytics from this would help businesses get powerful context.

When businesses get better context about their consumers, he said this would enable businesses to make better decisions in customer acquisition, product development, operations and customer support to start with. In the long run, behaviour analytics will help drive efficiencies across all business functions, once the organisation is able to map the complete consumer journey.

“The Near platform helps its users understand consumers based on their behaviour in the real-world.  Leveraging locations, transactions and other unique real-world signals from data partners, Near doesn’t just analyse ‘stay’ pings/POIs, but analyses movement, brand affinity and visitation. These are stronger signals to build shopper profiles than just the shopping habits based on online signals.”


As the platform provides insights into predictive human behaviour via data analytics, there will always be that concern about privacy. Shobhit pointed out that the Near Platform follows privacy by design and all data on the platform is hashed.


“The platform does not store or deal with PII (personal identifiable information), and all incoming data streams are consensual. We are GDPR compliant and compliant with local privacy laws in our markets.”


With the implementation of 5G imminent in most parts of the world, the speed and amount of data received will increase as well. Shobhit believes this development will support the Near data platform as faster speed combined with low latency will help them (and their data partners) collect, clean and analyse larger volumes of data within a short period.


In Malaysia, behavioural data is also highly being used by online shopping companies to study their customers’ preferences. The analysis is done mostly from looking at the shopping habits of customers on their websites, from the types of products they choose to how long they spend reading on a particular product before making a purchase. The data is then analysed and targeted to shoppers into buying more products.