One platform to unify data, activate insights and power your entire go-to-market.
Golden records, customer 360, single views and all that jazz.
10x the value, 1/10th the cost
Syncari simplifies your customer data stack by packaging all the tools you need into one no-code platform. The alternative? Hire 5 data professionals, then wait 6 months as they stitch together a mess of siloed solutions.
A hub-and-spoke approach
Stitch together data from any source with intelligent connectors that are constantly listening for changes. Define your customer data model and let Syncari manage cross-system transformations, ID mapping and schema changes automatically.
Get up-to-date data and insights to front-line teams. Syncari’s stateful multi-directional sync engine ensures fresh, unified data is accessible where your customer-facing teams actually work.
Trust your dashboards
Visualize pre- and post-sales data together from your entire GTM and product stack. Create a shared metrics library, sync reporting tools, and align systems and teams with a shared view of business performance.
Eliminate manual data work
Define rules and logic that dedupe, enrich, and normalize data across every connected system. Enforce data authority, trace transaction lineage and watch data confidence soar.
Deliver coordinated customer experiences by ensuring key signals are identified and activated across teams. Syncari workflows can access your entire customer data set.
One Platform, Many Initiatives
Point solutions solve point-in-time problems. Syncari is designed to grow with you as your needs evolve.
Customer Data Automation (CDA) solutions automate the complex and manual processes involved in aligning, analyzing and activating customer data. This allows organizations to efficiently manage their customer data, optimize customer-facing processes and experiences, and gain insights into customer behavior and preferences. Traditionally, this has been REALLY HARD for B2B companies where customer data is spread across contacts and accounts and sales cycles + onboarding can take months or years.
CDA requires unifying customer data from key sources — in sales, marketing, success, support, finance and product — into a central data hub. This hub then powers analytics through visual reporting and governs the flow of data and insights back out to operational systems. The distribution of data and insights in a scalable way is where most DIY approaches fall down — the warehouse or BI tool becomes the end of the data highway.
The goal of customer data automation is to improve customer experiences and support more confident decision-making by creating, maintaining, and distributing trusted customer data and insights to the people and systems that need it.
Customer Data Automation requires a novel approach that combines core capabilities currently spread out across multiple domains: iPaaS solutions, data transformers, cloud data warehouses, ETL, Reverse ETL and visualization/BI tools.
You can’t get to truly automated customer data by slapping together a bunch of disconnected tools, either. Only Syncari was built from the ground up to solve these problems with a platform specifically designed for business users.
Unlike traditional API-based connectors, Syncari Synapses deeply connect to top business systems and manage the impact of data and schema changes across the GTM stack. They’re fault tolerant and can be configured in a few simple steps – keeping your focus on your business, not the business of APIs and integration.
Multi-directional sync refers to a type of data synchronization (sync) between multiple systems, where data can be updated and exchanged in any direction, rather than just one-way or bi-directionally. This allows for data to be updated, synchronized and governed across your entire tech stack, creating a consistent view of customer data and key business metrics in every go-to-market system. Oh yeah, and Syncari holds a patent on this.
For those who want to geek out:
Our patented multi-directional sync engine provides a highly configurable unification, transformation and augmentation layer. It also handles data congruency and integrity. It can scale to manage thousands of concurrent data streams. These data streams are near real-time, are generated by our Synapses (see below), and all look the same.
We’ve also created a semantic layer (see: elastic data model) that allows the entire business to run using a single data language. This includes how you integrate, how you unify and transform key objects like contacts and accounts, how you define core metrics, and ultimately how you understand what changes these metrics by looking at customer data more holistically.
Data synchronization (sync) and data integration are related concepts but have some key differences.
Synchronization refers to the process of making sure that data is both available and consistent across multiple systems. This is done by regularly comparing the data in each system and updating it as needed to ensure that it remains in sync.
Data integration, on the other hand, refers to the simpler process of sending data from one system to another, often in a style that looks like copy/paste. When it comes to customer data, synchronization is a must-have.
An elastic data model is a type of data model that can easily accommodate changes to data schemas over time. For example, RevOps pros regularly add new fields to entities like contact or account. An elastic data model would incorporate that change without breaking any downstream processes or reports.
It is designed to be flexible and scalable, able to adapt to changing requirements and business needs without requiring significant overhauls to underlying systems or data architecture.