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How it Works


We ingest all your customer data at almost no effort to you. You do not need a centralised warehouse – we accept any feed, in any structure, then organise it to enable better decision-making. After validating every event, we organise so it describes a person – into actions (something you do), attributes (something you are) or entities (something you use), generating and keeping your complete relationship history with each customer.

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A client’s multiple and disparate data sources are uploaded via SFTP or an API (at any cadence) where they are transformed using fully configurable ingestion into our dynamic data model,  serialised using Thrift and Parquet formula (for optimum storage and retrieval) and finally stored in an immutable data store with a column-based structure for enhanced performance. Our open source ID generator assigns a monotonic ID to every event, guaranteeing sequential data order and enabling unification of disparate data sources at scale. Finally, our tech stack enables data to be joined and aggregated at scale and is lossless.

How it works


This is the bit no-one else does, the bit we have spent years perfecting. With blazingly fast data pipelines we transform raw data into human-like 360 profiles that accurately represent your customers as people – their habits, interests and motivations. Proprietary data science — bespoke algorithms together our Intent Graph find the patterns in your data to create a unique ‘data brain’ so you can see how customer behaviour impacts your KPIs.

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“InterestRank“, our behaviour to interest algorithm starts with the action data we have collected, and extract the interests from this data by referencing our proprietary Intent Graph. For example, a call to Topshop is mapped to the Topshop URL and referenced against the Intent Graph to extract related keywords and concepts. Our ‘interest inference’ algorithms provide the wider context Then our ‘interest inference’ algorithms provide the wider context for an action, e.g. High Street Fashion, Celebrity etc., so we can understand the ecosystem of related interests as well as the detail. Finally, each action is assigned an ‘action to keyword pairing, which we score for importance using multiple variables — frequency, popularity, source, recency and relevance for the individual user. The result: highly accurate interest scores on every customer.

How it works


Our visualisation has been designed from the ground up to help you make sense of what’s happening. Which, in turn, allows you to make better decisions for customers and the business. With a discovery rather than reporting focus, users explore customer behaviour asking their own business questions, whether that is identifying which competitors are capturing the attention of Netflix-obsessed new parents, or understanding exactly who to target for the next iPhone launch.

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Our Intelligence Dashboard answers your questions by giving you the power of performing sub-second queries over billions of events. This is possible thanks to three pieces of Intent HQ technology:

  1. Our blazingly fast data processing pipeline, which efficiently aggregates all the data available using the power of Spark.

  2. Our Profile API, backed by a specialised Elasticsearch cluster, which optimises each query to offer real time results.

  3. The Insights App, a single page application written with React that provides the end-user with a slick and fast user interface (UI).

How it works


Anticipate what individual customers want before they even know it themselves. Before long you will change customer perceptions, which as all marketers know is the holy grail of marketing. Oh, and you will also be able to forecast your quarterly results more accurately. Our AI based anticipation is at the cutting edge published research. From call centres to online; in-store experience to pricing — wherever a customer interacts with your brand there is an opportunity to create a more helpful interaction, based on everything the customer has done with you.

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Intent’s Customer AI is at the cutting edge of deep learning. We encode all customer data with unparalleled accuracy, creating a dense representation of the features in data. We use this to play out different sequences over time (t-1, t-2, etc.) to generate a range of probabilities that a customer will take a specific action at a specific point in time. We do this using all the data, not just a specific set of actions. The results are uncannily accurate. This means that for every customer, based on everything they have done, you can now predict what’s next and enable intelligent journey optimisation.