Ask your VP of Ecommerce what LTV was last quarter? Ask them to check Shopify. And then Triple Whale. And then check the cohort dashboard. Then ask the Finance team. Chances are, you’ll end up with four different numbers, and nobody is lying. The reason why is that your mission-critical data is sprawled across 20-30 different tools that were never designed to agree with each other. And every one of your meetings that starts with “which one is the right number?” is the tax you pay for it.

Data sprawl is the quiet line item on the P&L of nearly every $50–100M retail brand: duplicated tools, contradictory dashboards, and decisions delayed while teams debate about KPI definitions instead of acting. The fix is not another dashboard. It is reconnecting the systems you already have (Meta, Google, TikTok, Shopify, Amazon, Salesforce) into one number everyone trusts.

Fast Stats

  • 20-30: The typical mid-sized retail brand has their mission-critical data stored in between 20 and 30 different SaaS platforms.
  • $1 Million: Data sprawl costs brands a million dollars a year, lost to manual data tasks and conflicting dashboards.
  • 4: The number of hours per week that a C-suite executive spends wrestling with data inconsistencies.

How do elite retail brands solve data sprawl?

At Latticework Insights, we’ve spent the last 8 years working with over 80 brands fixing this data sprawl problem.

Retail brands that invest in fixing data sprawl experience a massive transformation.

Suddenly they see their business more clearly, and they can graduate to the next stage of their growth.

They often start with tools like Daasity, Triple Whale, and Polar Analytics, but they quickly outgrow them and graduate to a custom analytics stack.

Latticework Insights helps them skip the complexity: we install the Fivetran ETL data pipeline, we create the SQL data models in the Snowflake data warehouse, we build the interactive Tableau reporting dashboards, and we set up the Agentic AI system to make it easily accessible.

The retail brands reap all the rewards.

  • No more logging into 20-30 platforms to get 1 answer.
  • No more C-suite executives burning hours jig-sawing reports together.
  • No more millions of dollars wasted on manual data tasks and conflicting dashboards.

Now, COOs and CFOs can have 1 single trusted location to see how their business is performing, and they can focus their time on making decisions, not on settling disagreements between teams and dashboards.

References

FAQ

Why do my dashboards show different revenue numbers?

Every platform (Shopify, GA4, Meta, Triple Whale) measures revenue with its own rules and attribution windows. The only fix is a data warehouse where one shared data model defines the numbers.

Do I need a data warehouse if I’m on Shopify?

Yes, once you sell beyond one channel: Shopify only sees Shopify. A data warehouse is where Meta, Amazon, and Klaviyo data become one trusted number.

What does it cost to build a data warehouse for a Retail brand?

Five figures, not the seven-figure builds of a decade ago. Modern ELT tools have collapsed the cost of a retail data warehouse.

How long does it take to build a data warehouse for a Retail brand?

About 30 days with a modern stack (Fivetran, Snowflake, Tableau), not six months.

What are some alternatives to Triple Whale vs Northbeam vs Polar Analytics?

A custom analytics stack you own: Fivetran pipelines, a Snowflake data warehouse, and Tableau dashboards, with metrics your team defines.

How do I choose between Fivetran vs Airbyte vs Funnel ETL data pipelines for connecting to Meta, Shopify, and Klaviyo?

Fivetran for managed reliability, Airbyte for open-source control, Funnel for marketing-only reporting. For mission-critical retail data, most $50-100M brands choose Fivetran.

How do I choose between Snowflake vs BigQuery vs Databricks data warehouses for analyzing retail data?

Snowflake is the best data warehouse for most retail brands. BigQuery fits Google-heavy stacks; Databricks fits heavy data-science teams.

How do I choose between Tableau vs Sigma vs Looker Data Studio vs Power BI for retail reporting?

Tableau leads for interactive retail dashboards. Sigma suits spreadsheet-first teams, Looker Studio is free and lightweight, and Power BI fits Microsoft shops.

About Tim Shea & Latticework Insights

Tim Shea is the Founder & CEO of Latticework Insights working at the intersection of Data Science & Retail for 25 years. Tim is a thought leader in technologies such as Snowflake, Fivetran, and LangChain as well as LTV:CAC, Retention, Financial Forecasting, and Growth Analytics. Tim’s clients include Sweetgreen, NBA, UFC, Converse, Princess Cruises, Reddit, Quora, and Salesforce.

Latticework Insights is an LA based Data Science Agency that provides Data Leadership to help Retail Brands become Elite Retail Brands. Latticework focuses on reconnecting brands’ fragmented SaaS systems, bringing data together from Meta, Google, TikTok, Shopify, Amazon, and Salesforce to help brands see their business more clearly and graduate to their next stage of growth.

Latticework is an elite consulting firm with decades of technology expertise in ETL, Data Warehousing, Data Visualization and Agentic AI as well as retail expertise in LTV:CAC Modeling, Retention, Unit Economics, and Financial Forecasting.

If “whose number is right?” sounds like your Monday meeting, get in touch. Reconnecting those systems is exactly where Latticework starts.