What is a system of engagement?#
A system of engagement (SOE) helps organizations communicate, collaborate, and interact with customers and team members. In contrast to systems of record that store and manage data, SOEs prioritize human interaction and engagement.
Systems of engagement are focused on helping you interact with your customers via more personalized, seamless interactions across the various touchpoint of the customer journey.
A CRM, for instance, is both a system of records for customer data (each record contains company or contact information) and a system of engagement that provide a user-friendly interface to collaborate and engage with customers.
Traditionally, the main advantage of grouping these two systems is creating a seamless link between customer engagement and back-end processes.
But, with the sophistication of go-to-market strategies, things are different now. We live in an unbundled era where you will have idiosyncratic tools for each use case. According to BetterCloud, an average SaaS company uses 80 different SaaS apps.
For instance, let's take a typical stack for SaaS:
You have Salesforce used as the system of records for sales; the interface and collaboration layer is a tool like Dooly that sits on top of Salesforce to provide better UI. You'd have Salesloft or Outreach for sales Outreach and Braze or Hubspot for customer engagement. When it comes to reporting or analytics, you'd do it on Looker or Metabase.
Yes, Salesforce is still used today as the system of records for sales data, but it can no longer be considered the single source of trust for your business.
The reason is that a company uses too many systems of records, and each department has its favorite ones, causing internal misalignment and conflicts. Also, Today's SaaS locked-up architecture does not help companies embrace the ever-growing sources & complexity of data.
To make sense of all those data, modern companies turn to Cloud Data warehouses like Snowflake to unify and reconcile their data from different tools.
CDWs are becoming the single source of trust to align teams internally.
Tomorrow’s system of engagement
Now, listen up: question for you guys!
Why do we have software in Business Intelligence that sits directly on top of the data warehouse (👋 Hello Looker or Metabase) and, on the other side, we are still using API or reverse ETL to sync data back to our (siloed) operational tools?
You might be wondering what’s wrong with API sync & reverse ETL?
To answer shortly, try to sync 6 million customer records daily to keep your CRM up to date, and check your invoice at the end of the month. Unfortunately, there is an inefficiency in the way we treat data today.
The real question is “why should we pay multiple time for the same data?”
As most SaaS are record-based, you need to pay this customer record in Braze, in Intercom, in Zendesk, in Hubspot - basically in every go-to-market and customer support application. Each tool stores a copy of your customer data in its proprietary system.
Cloud-based storage is cheap. Storage inside of SaaS tools … is not
Isn’t that crazy?
If I want to make a techy analogy: if you have multiple times the same lines of code in your script, you did not factorize well and can write code more efficiently.
Another one for marketers: in a landing page, if you have several blocs answering the same need, it needs you can craft a better persuasive flow. You should not have repetition/ duplicate blocs.
If you agree with this, you should not pay "duplicated cost" for the same record.
I won't discuss other limitations around data security and observability by pushing your data to an external platform.
On the benefits side, beyond getting a common single source of trust, data and revenue teams would enjoy specific advantages, security and ensuring reliable data for IT teams, and the 360° view of the customer for go-to-market teams. In addition, implementating such engagement systems is seamless as those softwares does not own the data.
For Data Teams:
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Data integrity: Engineering team ensure that data are reliable
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Data Observability: enterprise-grade control provided by modern cloud data warehouse to control and govern access
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Data Security: You won't have a third party storing your data
For revenue Teams:
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Data accessibility: No more bottleneck to leverage CDWs power
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Flexibility: You can leverage custom business definitions and entitities
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Data quality: Orchestre campaign or operation process on reliable data
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Cost efficient: You don't pay multiple times for the same data
Why haven't we been able to replicate Looker's success in business intelligence (BI) for data operationalization?
By data operationalization, we mean ensuring that accurate and timely data is made available to systems that can use it to drive action, such as in advertising, product usage monitoring, customer engagement, and sales automation.
This is where we stand at Cargo: We are the application layer on top of where your data lives: the data warehouse.
As CDWs are now considered the reliable source of truth for modern companies, we need to build the missing piece: software built from the ground up to leverage data warehouse power and bring business folks, the biggest data consumers, on top of this new source of truth to let them orchestrate campaigns and build operation processes.
It will also help unite data and business teams to build applications that drive revenue using the same source of truth.
✔️ According to Sirius decision, B2B businesses that align their revenue engine grow 12X to 15X times faster than their peers and are 34% more profitable
No more siloed and disparate data, no more internal battle with each department claiming to have different data.
Welcome to the world of alignment and performance.
👉 Interested to learn more? Join the movement now
MaxJan 1, 2024
