HighRoad Spark: An Evolution in System Integration
As more and more associations work to become data-driven organizations, they keep running into the same problem: integration. Associations have the data. The problem is getting all of that data into one place.
Data integration is tricky in most circumstances. It can be really tough for associations, as the majority of commercial tools don’t work with Association Management Systems (AMS). And integration isn’t just an IT problem either. Without the right data pipelines in place, you can’t run data-driven marketing campaigns or execute member-focused strategies.
That’s why we here at HighRoad Solutions have been working tirelessly to help associations unify their data. Our go-to tool has been the Plus Connector, a neat piece of software that enables fast communication between an AMS and another data source.
But now it’s time for Plus Connector to slowly stand down. The next phase of integration is soon arriving. We call it HighRoad Spark.
Each element of the stack holds important member data. Your AMS has full membership details, your email automation platform tracks engagement, and the learning management system contains details of programming consumption. To understand your members, you need to bring all of this data together.
And this is where HighRoad Spark comes in. Spark is a software platform that sits in the middle of your martech stack, coordinating data movements between systems.
Say, for example, that you want to sync your marketing automation platform with the data in your AMS. Typically this involves some coding and working with APIs.
With HighRoad Spark, the process goes like this:
- Connect Spark to a source: Connecting Spark to your AMS is easy. Just select your system from the menu, grant authorization to Spark, and you’re good to go.
- Connect Spark to a destination: This is equally straightforward. Just select your marketing platform from the menu, authorize it, and you’re done.
- Create a mapping: Use the interface to tell Spark how to match your AMS database with your marketing platform database. For example, your AMS may have a column called LAST_NAME, while the marketing platform has a column called SURNAME. Mapping lets Spark know that it should take data from LAST_NAME and insert it into SURNAME.
- Run the integration: You can schedule automatic integrations to run at regular intervals, or can click a button and start an integration right now.
You only need to go through this process one time for each integration. Once you’ve set up a functioning pipeline, you can let it run in the background, or execute it at any time with one click.
When you run an integration, Spark goes through three steps:
- Extract: Spark accesses the source database (your AMS) and pulls out all relevant data.
- Transform: Spark holds the extracted data in an intermediate database. Here, Spark can perform data transformations, such as mappings or integration with other data sources. You have full visibility of these processes, so you can immediately identify and resolve any issues.
- Load: Once the data is ready, Spark will push it through to the destination. Your destination database is now fully updated and ready to go.
This process will be seamless and quick. From your perspective, it’s a matter of clicking the button and waiting for the integration to complete.
HighRoad Spark makes some substantial improvements to the old Plus Connector, as well as offering some brand-new features. Some of the main benefits are:
- Empowerment: Take complete control over the flow of marketing data without having to explain your requirements to the IT team.
- Centralization: Bring disparate data sources together in a single location so you can understand your members on a demographic, psychographic, and behavioral level.
- Instant gratification: Set up the views you need and run the integrations you want, without having to wait for IT to process your ticket.
- Transparency: See everything about how data flows from A to B within your systems. Identify data loss or bad mapping before it becomes an issue.
As well as that, you’ll deliver substantial value to your IT team, such as:
- Time savings: Minimize the time that IT spends on processing routine data requests.
- Centralization: Reduce data redundancy and fragmentation within the marketing tech stack.
- Flexibility: Build a scalable infrastructure where components can be plugged in or out with ease.
- Data integrity: Build credibility by creating reliable, sustainable data structures.