AllSight's platform creates a next-generation customer 360 that connects billions of data points across disconnected silos to uncover insights for business users across a variety of use cases. To solve the problem, companies require fresh approaches that consider all the tools, processes and data across the customer journey. AllSight lowers the complexity for companies that require the ability to dynamically maintain a single source of truth about each
The 451 Take
AllSight experienced exponential growth in the past
Businesses have made investments in transactional systems and MDM since about 15 years ago to create a complete customer profile, but they failed to deliver a complete 'single source of truth.' There are continually new sources of data and applications that add
It continuously synthesizes, learns, adapts, improves and automates in real time, relating and linking data and creating a dynamic customer graph with a high accuracy. The ability to link all this new data is critical. Synthesis understands and creates context from raw data (fragments and unstructured data) providing demographic, product and interaction history, and a full view of the customer journey. It's based on both columnar and graph technology, supporting the scale and speed needed for today's data volumes. Graph databases allow organizations to traverse and analyze information and insights across customers, organizations
As we have mentioned before, CIPs are not just about the data, but also have the potential for delivery of dynamic rich media content, including images, videos
AllSight synthesizes data that dynamically links customer-customer and data-customers using an optimized mixture of matching techniques. As it ingests and synthesizes more data into the customer 360, a CIP must also become more intelligent in identifying important trends and information for each customer, and better at summarizing the important intelligence for specific business users. Synthesis and reasoning must work in balance to ensure the CIP is usable: as more data is synthesized and the customer 360 becomes deeper and richer, the CIP must get better at summarizing the important intelligence for specific business users.
Automated reasoning helps make inferences and enrichments on each customer profile, and also helps line-of-business users predict the customer's future actions such as churn, propensity to buy, proximity and location. It provides a deeper understanding of individual customer journeys and unique interactions, combined with transactions, to accurately understand and improve customer experience. AllSight can be used as a stand-alone product with pre-built dynamic user interfaces for specific use cases, or deployed as a headless architecture, which can then enhance existing applications for sales, marketing, customer care and commerce. There are three major areas where AllSight recently updated the platform:
- Advancements in genetic machine-learning algorithms. AllSight uses a variety of machine-learning algorithms with a higher degree of accuracy, based on specific use cases such as data matching, which weights the probabilities of a match or non-match based on the relative weightings of attribute matches, and their individual probability of a match or non-match outcome. Its genetic algorithm is another differentiated capability that applies techniques such as survival of the fittest, crossover, and mutations on large population sizes for many generations, to learn the optimal or near-optimal approach.
- Enhancements to dynamic user interfaces for marketing and customer service and support. AllSight has a variety of dynamic, humanistic UIs, such as the Customer Interaction Predictor that displays products a customer may be inquiring about, previous interactions, product-level sentiment, and proactive offers and cross-sell incentives. This visibility enables CSRs to improve customer satisfaction by increasing
first-call resolution,and providing more relevant offers that shift contact centers from cost centers to service centers.
- Expansions in pre-built customer-centric use cases. Top areas include marketing, commerce
andoverall customer-experience use cases for improved micro-segmentation and targeting for real-time individual customer journey optimization, content personalization tailored to individual buyers' journeys, voice of the customer and survey feedback, shopping cart analysis, next-best-action for customer service, and attrition modeling and retention. All initiatives rely on specific components of a CIP, and extend existing software and/or data management investments. AllSight's CIP is particularly well suited to addressing multiple use cases and initiatives due to its ability to create and manage multiple perspectives of the same customer – or unique business views for specific use cases, users, geographic or business unit divisions – enabling different, tailored views of the customer for each user.
MDM major players with expertise in customer management, including Informatica, Oracle, SAP
There are also MDM providers that offer more in-depth expertise for creating a 360-degree view of the customer such as Semarchy, Stibo Systems
Sheryl Kingstone leads 451 Research’s coverage for Customer Experience & Commerce, which covers the many aspects of how customer experience is a catalyst for digital transformation. She oversees the company’s coverage of a variety of customer experience software markets spanning ad tech, marketing, sales, commerce
Jeremy Korn is a Research Associate at 451 Research. He graduated from Brown University with a BA in Biology and East Asian Studies and received
Aaron Sherrill is a Senior Analyst for 451 Research covering emerging trends, innovation