We’re excited to announce our partnership with Dreamdata, a leader in B2B Revenue Attribution. While Hightouch helps sync data from your warehouse to business tools, it is most useful when your warehouse data is transformed, modeled and ready to be activated. Dreamdata helps with this by doing the heavy lifting for tracking, collecting, cleaning, and merging of your revenue attribution data.
Your business teams need modeled data in the tools they live in day-to-day. The combined power of Dreamdata and Hightouch bridges the gap between data and business teams to enable everyone to use modeled data however they need.
The power of Dreamdata
While the warehouse is the source of truth for modern businesses. But what if the data sitting in your warehouse is dirty? Duplication, incomplete values and null values are unfortunately too common. To combat this, Dreamdata’s unified data platform helps structure your data warehouse to make your querying easier, and gives your data scientist/data analyst time to focus on what matters: not on cleaning your data.
Dreamdata has a few key functions:
- Tracking, identifying, and storing customer data: Dreamdata provides a Javascript to unlock tracking and identification across your website and apps
- Unifying and cleaning data: Dreamdata maps certain combinations of UTM parameter values to a customized source and channel name. For example, mapping a utm_source value of hs_automation to the HubSpot source and Email channel. Their algorithm then removes duplicates and irrelevant tracking.
- Merging data: Finally, they provide tools for you to map activity back to a given company, by using either email or Reverse IP lookup.
How can you use Hightouch and Dreamdata?
Dreamdata provides a clean, unified customer profile in your warehouse. Using this modeled data with Hightouch, you can sync to tools like a CRM such as Salesforce or HubSpot, Marketing Tools like Marketo or Google Ads, and most other SaaS applications.
If you're a Dreamdata customer, adding Hightouch will allow you to activate your Dreamdata models and enrich the tools your business relies on. Here are some example use cases that our shared customers use:
- Improve top of the funnel awareness by creating segmented and personalized marketing campaigns in tools like ad platforms (ex: Google Ads), email tools (ex: Mailchimp) and marketing automation platforms (Pardot, Marketo, and Omnisend)
- Improve acquisition and pre-sale rep efficiency by enriching your CRM records (ex: Salesforce, HubSpot) for automation and providing full visibility of everything a prospect is doing on your site and application.
- Decrease churn by sending behavioral data to your Customer Success tools (ex: Gainsight) so your reps always know exactly what is going on with each account.
For the reverse, if you're a Hightouch customer, Dreamdata will collect, clean and structure your data warehouse. That way, you can send data with Hightouch that you’re 100% confident in (without needing to write massive queries with dozens of joins). Simpler queries empower your business users to self-serve and allows data teams to focus on more advanced insights. Everybody wins.
Self serve your data, without engineering help
With modeled data from Dreamdata, querying becomes much easier. For instance, say you want to extract an audience which contains only emails that visited the pricing page at least once in the last 7 days. A complicated SQL challenge right? Not with Dreamdata. With Dreamdata's modeled data, your query would look as simple as this:
WITH pricing AS (
SELECT
email,
MAX(timestamp) as last_visit
FROM
`dreamdata.dreamdata_io.events`
WHERE
email is not null
AND event in ('page_view')
AND url like '%/pricing%'
GROUP BY
email
)
SELECT
c.*,
last_visit
FROM
`dreamdataio.hightouch.all_contacts` as c
INNER JOIN
pricing as p on p.email = c.email
WHERE
c.opt_in_event is TRUE
But what if you aren't familiar with SQL? Hightouch's visual audience builder allows business team members to visually filter modeled data through an easy-to-use yet powerful UI (without needing to know SQL). This enables business teams to self-serve while still having the guardrails of modeled data, such as marketers defining audiences to target in lifecycle marketing or paid ad campaigns.
