Marketing data engineering by Datics AI · MarTech service
Crawlers, searchable indexes and streaming pipelines that turn outside signals into data your product can rank and score.
AI is only as good as the data under it. We build the crawlers, indexes and streaming pipelines your product needs, on your stack and versions, so ranking and scoring start from clean, current data.
Built in your codebase and tested in your vendors' sandboxes.
Data engineering for MarTech and ad tech products
- Searchable before enriched. Your existing lists loaded into a search index first, so there is a working result to judge.
- Enrichment crawlers. Page data, public follower counts and traffic rank added to each record from public store websites.
- Dashboards your team runs. Filter by niche or segment and follow growth over time, without an engineer.
- Streaming logs. Website logs analyzed in Spark from a Kafka stream and written where each consumer reads.
What it does
What the integration service covers.
Data work under MarTech and ad tech products: crawlers that add page data, public follower counts and traffic rank to each record from public store websites, searchable indexes and dashboards non engineers run, and streaming log pipelines on the stack you have.
Searchable before enriched
Your existing lists loaded into a search index first, so there is a working result to judge.
Enrichment crawlers
Page data, public follower counts and traffic rank added to each record from public store websites.
Dashboards your team runs
Filter by niche or segment and follow growth over time, without an engineer.
Streaming logs
Website logs analyzed in Spark from a Kafka stream and written where each consumer reads.
How it works
We start from the data you have and make it searchable, then add outside signals with crawlers, or work inside your streaming stack as it stands, writing results to Elasticsearch, MySQL or the stores your product reads.
Built on a store index and crawler we have built for a company that evaluates e-commerce brands, and weblog pipeline work for an audience data company.
NOLK Enterprises Inc.
Market data · Store intelligence
Thousands of online stores indexed from spreadsheets, compared by traffic and social following
The store list sat in four spreadsheets nobody could search. Now every store is indexed, enriched from the web and compared in dashboards.
An audience data company
Audience data · Streaming weblogs
Website logs stream through Spark into Elasticsearch and MySQL, ready for recommendations
An audience data company had website logs streaming in but needed them analyzed and stored for recommendations. We did it on its own stack.
SenTrac
Social data · Collection within API rules
Campaign reports use only the data each platform allows, refreshed within its limits
Social APIs are gated, capped and change often; we built SenTrac's data layer so each platform's rules and limits hold and reports stay current.
Why it sells
What the integration service makes possible.
Best fit: Any marketing, audience or ad tech product that ranks or scores outside data.
Controls
What the integration touches, and who approves.
Built in your staging; nothing changes in your product unless your team merges it.
Who uses it
Your data, product and engineering teams
What it connects to
Your lists and logs, public store websites, search and relational stores
What a person approves
Your engineers merge every change; we work on your installed versions
How to get it
A fixed-scope integration, then it runs.
Scoped in the Product Review and quoted before we start. Add more only if you want it.
First · Scope · fixed quote
One piece of work, scoped
- Your staging
- Pull requests
- Your team merges
- Built and tested in your staging
- Reviewed by your engineers
- Monitoring before go-live
Then · Live in production
A finished product, yours to run
- Fixed quote
- Tested before launch
- Switch per agency
- A finished, working Marketing data engineering in your product
- Runs in your cloud, under your name
- Fixed quote, agreed before we start
Optional · Add more later
Only if you want it
Modules it feeds:
- Each one quoted on its own
- Nothing ongoing unless you ask
Already built or tried AI? Get it scored with the AI Scorecard. Need something else? Start with a Planning Sprint.
See the integration service on your own product.
Bring your product and the systems your agencys run. In 30 minutes we look at what the integration would cover and what it would take.
Calls run in US Central time. No generic AI presentation: we discuss your product, users and production constraints.