Unveiling ABX, Airbloc’s real-time personal data exchange platform for enterprises
To further cater to enterprise needs with regards to data exchange, we are happy to unveil our new product — ABX, a customer behaviour-driven & real-time personal data exchange platform based on blockchain technology.
The following topics will be discussed in this article. Click on the following headers to skip to the relevant sections.
- Summary of ABX’s features
- Ideation and business imperative behind ABX
- Rationale for incorporating blockchain elements into ABX
- Adoption use-cases of ABX
- Go-to-market and business strategy
ABX is a further upgrade with newly introduced features and expanded use-cases compared to our previous product Databloc. Aside from being a customer data marketplace (which was the original concept of Databloc), ABX also serves as a real-time Data Management Platform (DMP) that can be used by enterprises for digital marketing and business intelligence.
Summary of ABX’s Features
To set ABX apart and to increase its market adoption rate, a few key unique features are serviced to enterprises:
1. Actionable and real-time customer behavioural data to enable enterprises to exchange data in real-time, and send on real-time customer behavioural data.
2. Enterprise-grade data exchange scalability capable of handling high volumes of transactions in real-time. [Read more on how we do this HERE]
3. Immediate data utilization through data streaming to allow enterprises to subscribe data from ABX to their own internal business intelligence or marketing platforms to launch personalized or targeted marketing campaigns to relevant customers directly.
4. Campaign performance tracking and data effectiveness measurement for enterprises to analyse which of their purchased data used for execution in the form of targeted marketing campaigns are useful for user acquisition and conversion.
5. Auditable source of data provenance through blockchain technology to ensure the legality and legitimacy of data exchanged.
6. Ricardian contract and smart contract integration to ensure that reward flows are automatically enforced, instantly and fairly shared with data consumers, data providers, and data subjects (individuals agreeing to monetize their data).
7. ABL token integration with expanded use-cases for data consumers, data providers, and data subjects. [More will be explained in subsequent articles. Stay tuned to our announcements!]
The idea and business imperative behind ABX
In contrast to ABX, traditional DMPs are customer profile-driven & time agnostic driven by static customer data. The way these DMPs work is to gradually aggregate static properties of the customer such as age, gender, installed applications, liked products, tagged items etc. After summing up the static properties, customer profiles are grouped into segments which are used for targeted advertisements or business intelligence.
The problem is that this way, defined segments might not correctly reflect the actual customer intent or context because these static properties tend to decay over time or are not actionable enough since static properties do not cover implicit customer behaviours, intent, or context.
For example, solely relying on data that one customer has installed a wedding application might be of limited use to wedding companies because the customer might already have already finished the wedding. There needs to be more relevant non-static data to accurately reflect actual customer intent and context.
Reactions to customers behaviour through relevant product/service recommendation in the form of targeted marketing campaigns should be always timely ; in real-time to capture their intent, behaviour, and decision-making context.
As such, time delta is a very influential piece that can be used by companies to immediately react to customers’ intent and decision-making context. Suppose one customer just finished eating lunch in a restaurant, the TTL (Time-to-Live) of interpretation of customer behaviour data is very short since customer is moving to the next destination within 5 minutes. It is useless to recommend something to the customer after 5 minutes.
Second, the majority of useful customer behaviour data are implicit and are not usually captured by DMPs. For example, even though a 70-year old grannie does not seem to like hero movies by her profile on a DMP, if this grannie watches many hero movies, we know that she has a preference for hero movies and should recommend one. In this sense, behaviors, not the profile, always reveal the true intent of the customers.
In light of these issues, we are developing ABX, a new form of behaviour-driven DMP that allows enterprises to collect and exchange data between themselves to reflect customer behaviours in real-time for more effective targeted marketing campaigns and business intelligence.
Reacting timely to customer needs is integral. In order to increase the likelihood of a customer buying a certain product, issuing discount coupons right after we know that the customer has an intent and is interested in purchasing a computer notebook will significantly increase the chance of the customer buying that product in the coupon issuer’s marketplace rather than other competitors’ marketplace.
Discovering the right customer intent is also highly important. By looking into customer’s profile on traditional DMPs, we have low possibility of discovering accurate and updated customer intents, but by looking into customer behavioural data such as viewing product, searching certain product keywords, or even purchasing related products will give the system enough information to compute the recommendation result with best accuracy.
Rationale for incorporating blockchain elements into ABX
Aside from the above mentioned features, we are also incorporating elements of blockchain into ABX. Increased emphasis on stricter regulation with regards to consumer data privacy and personal data ownership impose new procedural obligations for organizations processing personal data to return more rights to data owners.
As such, ABX will leverage blockchain technology to help facilitate more transparent data flows between data owners, data providers and data consumers by creating fully auditable data supply chain. Transactions in the form of exchange details, purchases, bids, and data flows will all be recorded on-chain. This is done with the ultimate goal of returning data ownership back to data owners, and to allow data consumers to purchase explicitly consented data with an auditable source of provenance.
There are 3 major overarching applications of blockchain in ABX:
1. Auditable source of data provenance through blockchain technology to ensure the legality and legitimacy of data exchanged. Data can only be exchanged when data consent has been registered on the blockchain. ABX automatically checks for explicit consent registration on the blockchain before data exchanges or purchases can be made.
2. Ricardian contract and smart contract integration to ensure that reward flows are automatically enforced, instantly and fairly shared with data consumers, data providers, and data owners (individuals agreeing to monetize their data).
3. ABL token integration with expanded use-cases for data consumers, data providers, and data subjects.
More of these will be elaborated in subsequent articles. Stay tuned to our releases and product updates!
Adoption use-cases of ABX
There are several ways that data on ABX can be used for targeted marketing campaigns and business intelligence:
1. Issuing time limited and customized product/service discount coupons (that are tailored to customers’ purchase intent).
2. Sending personalized messages (Push notifications, email, text messages, etc.) that are timely and reflective of customer interest.
3. Exposing personalized advertisements (targeted per each individual)
4. (TBD) Providing real-time recommendation engine as a service (RaaS) (that use third-party data to reveal hidden agenda of the customer.
Because ABX is a real-time data exchange platform, delivery timing of these marketing campaigns or business intelligence feedback can be customized to a few seconds to maximum few days (customizable) after occurrence of certain user behaviour.
