Tim Shea is the founder and CEO of LatticeWork Insights, where he has spent a decade helping DTC and retail brands untangle data spread across dozens of disconnected platforms. Before that, he built a 25 year career across software engineering, data, and advertising, including years selling data solutions into major media agencies.
Most brands have data trapped in Meta, Google, TikTok, Shopify, Amazon, QuickBooks, Salesforce, and Klaviyo, and stitching it together every week eats up expensive leadership time. Tim argues this manual reporting cycle is a hidden cost most founders never account for.
The conversation covers when a brand is actually ready to invest in analytics, why LTV and CAC are stories rather than single numbers, and why he tells clients to fund analytics the same way they fund ad spend, expecting a real return. Tim also breaks down where AI genuinely helps data teams and where it creates expensive slop instead.
Listeners walk away with a clearer framework for knowing when their reporting problem is actually a decision-making problem, and what it costs to keep ignoring it.
Website: https://expanio.com/
Podcast website: https://expanio.com/commerce-untold-podcast/
Eitan Koter’s LinkedIn: https://www.linkedin.com/in/eitankoter/
YouTube: https://www.youtube.com/@CommerceUntold
Guest: Tim Shea, Founder and CEO, Latticework Insights
Tim Shea’s LinkedIn: linkedin.com/in/sheanineseven
Milked Media: https://latticeworkinsights.com/
Key Takeaways:
- Manual reporting across 10-30 disconnected platforms quietly costs brands far more than the software itself
- LTV and CAC are not single numbers, they’re stories shaped by cohort, channel, and buying behavior
- Analytics should be funded and measured like ad spend, with an expected return above one dollar per dollar spent
- The biggest unlock often comes from getting a company to agree on one true north metric, not adding more dashboards
- AI is useful in the hands of people who already know how to architect a solution, and dangerous in the hands of people who don’t
- The right time to invest in data infrastructure is after product-market fit, not before it
Chapters:
[00:11] Introduction and meeting Tim Shea
[00:37] Getting thrown out of a sales pitch and the origin of LatticeWork Insights
[03:00] Listening to customer pain over pitching product
[04:25] The real cost of data spread across 10-30 platforms
[05:03] Manual reporting and the hidden cost to leadership time
[08:58] Blending data analytics with intuition
[09:32] LatticeWork’s process for a new client engagement
[13:14] When brands should NOT reach out, and when they should
[16:36] Common implementation challenges and getting teams aligned
[18:57] Why analytics should be funded like an ad spend
[21:44] Where AI actually helps, and where it creates slop
[26:40] What brands get wrong when working with agencies
[29:49] Tim’s ideal customer
[31:13] How to find LatticeWork Insights
[31:58] Closing thoughts
