Marketing Alchemy: Turning Your Data Into Customers

Here’s the broad playbook I use for data marketing, particularly for putting out high-frequency data updates. One caveat before we dive in: using internal data externally should be done carefully. Never expose customer data or anything that could be perceived as too sensitive. It’s not worth it.

The Goal

Build an owned audience with high retention and engagement that consumes product-generated data, improving brand visibility and lead flow in the process.

Why Data?

1. The noise is deafening. There are more people (and AI) than ever battling for your users’ eyeballs. Generic content won’t help you stand out.
2. Data delivers what readers actually want. Open up the Wall Street Journal, the Economist, or the New York Times. A shocking number of articles cite corporate data. This isn’t lazy journalism; companies are sitting on incredibly unique datasets.
3. Data filters your audience. The right data is fascinating to the right users and meaningless to the wrong ones. It’s a natural noise filter.

The Approach

Leverage internal data (relevant to your product) to create a recurring, relatively low-effort content channel that drives unique value to users consistently.

Since this is an owned channel, distribution happens across many surfaces, but the core goal is capturing either emails (via newsletter) or website visits (via self-service data). You’re using insights from your data to build an audience. That’s it.

This is typically easier in B2B, where users are informed buyers trying to make (or justify) decisions with incomplete information.

The Zillow Blueprint

One of the OGs of this approach is the Zillow Home Value Index. It works because:

• They had unique aggregated data on household sale prices
• Publishing it was valuable — at the time, firms were charging for the same data
• They created tiered data (city-specific indexes) that segmented users
• Regional indexes enabled a micro-regional media strategy
• It brought customers (agents) and media directly to them

Other examples: Google Trends, Semrush Sensor, AppsFlyer’s Performance Index, LinkedIn’s Workforce Report, Spotify Wrapped, and Uber Movement.

The Data Audit

Before you build anything, figure out what you have.

Assess what keeps your users up at night, find where that overlaps with your unique data (even a secondary signal), and look for high variance. Bonus points for strong SEO search volume. A good litmus test: would a reporter covering your sector be excited to get this data?

Don’t overthink it. The overlap between what you know and what your users want to know is usually closer than you think.

Starting Without Unique Data

You can bootstrap with aggregation or curation. Many popular tech newsletters aggregate links and editorialize on top. An alternative: aggregate external data, like a monthly newsletter on funding rounds or M&A in your sector.

This builds an initial audience and establishes credibility for the person signing the emails. Think carefully about who that person is — if this works, they’ll be out there a lot, talking to media and generating insights.

The Three Tiers: Building Your Data Engine

Tier 1: Medium Frequency, Medium Value

Find a few flagship indicators you can distill from your data. Ideally weekly, but monthly works. This is probably a benchmark indicator of industry health, possibly with some segmentation. It’s a top-of-funnel metric you can editorialize around — interesting, but nobody’s pulling out their wallet over it.

For me at Freightos, this was monthly freight rate averages across global trade lanes. Interesting as a general industry number, but useless for actual purchasing decisions.

When you launch, backfill historically so you can offer QoQ and YoY insights.

Your number one goal: inform your readers using your data.

Distribute via email newsletters aggressively promoted on social. When you’ve validated the data is right, bring in the media. Segment a separate, more concise email for reporters. Compensate for lower frequency with stronger editorial — interview thought leaders, newsjack events with your data, optimize landing pages for signups, and put the data in email signatures.

This tier is your hook. It validates interest, builds your presence, and becomes the number cited at industry events.

Tier 2: High Frequency, Medium Value

Now step it up. Your readers are hooked — if you miss an update, they notice. Go weekly.

Playbook it or it’ll eat your time. Find 3-5 sub-data points that are more granular and more actionable. This is the shift from the Zillow US index to the San Francisco market index — irrelevant in New York, super-relevant on the West Coast, and interesting to everyone when comparing SF, Miami, and NYC.

Template the editorial. Keep a paragraph or two in each email, enough to slot in a product plug underneath. Start each email with a personal line from the writer. People follow Anderson Cooper, not CNN.

If it’s working (30%+ open rates, 10% WoW subscriber growth), start layering in upsells. But keep this close to your product — if the data is too far removed from what you sell, the conversion path breaks no matter how strong top-of-funnel looks.

Now expand your formats:

• Programmatic SEO pages targeting the long tail (my holy grail — thin pages with 3-5 data points, Mad Libs-style variable copy, and a product CTA)
• Weekly or monthly webinars
• Blog posts
• On-demand analyses for media
• Data points baked into sales decks

Tier 3: Self-Service Data Portal

The natural extension, when this really works, is a self-service website. It becomes the SEO and backlink center of your data efforts while bringing users directly to you. From there, it evolves into separate data monetization and/or product integration.

Data at this point covers more dimensions (geos, verticals) and shifts toward daily or real-time. The user funnel becomes:

1. Signs up for newsletter
2. Signs up for data portal
3. Sees product ad in newsletter/portal and reaches out — or sales reaches out based on engagement signals
4. Revenue

Bringing It Home

Throughout this entire process, pay attention to events inside and outside your business that justify a quote + data point for a media pitch or social post. Sprinkle money-shot slides into presentations. Incentivize subscribers to share. And always give data out for free to media and analysts — if it works well, let them embed charts on their own sites.

How This Played Out at Freightos

Before we had data, I built the audience by tracking 10-15 industry analysts on Twitter, capturing every link they shared in a Google Sheet, and reviewing it monthly for a curated industry newsletter.

When we had enough data, we started pushing monthly freight price updates on core trade lanes. We layered in one-off analyses of specific events — a typhoon closing a port, a canal blockage — pairing ongoing data points with timely editorial.

We aggressively grew subscribers and hiked up frequency. The core product became a weekly summary of global freight, compiled from industry publications (with credit), paired with data tables and charts. We forked it into a media-focused newsletter (with pitches for launches and events) and a customer newsletter. Each had a personal Freightos intro and a product ad at the bottom.

The flywheel: we pushed data to media, they cited it, their readers subscribed. Within 6-12 months, our data was showing up in major industry presentations.

Then we built a dedicated website with programmatic landing pages for each trade lane. This triggered an SEO snowball — reporters searching for shipping data found us organically, cited us, improved our authority, and sent more traffic. We upsold reporters on adjacent datasets (“we also have transit time data”) and productized whatever they kept asking for.

By 2023, Freightos had:

• 50K+ newsletter subscribers with 40%+ open rates
• A high-traffic data website driving dozens of enterprise registrations daily
• A separate data sales business with customers like Amazon and UPS
• Hundreds of mainstream media mentions annually, the vast majority no-touch