Streamlined Metrics, Data Pipelines, and Sources of Truth with Analyste

December 1, 2021
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Blue background with the Tydo and Analyste logos with white text that says "Distilling data"

Streamlined Metrics, Data Pipelines, and Sources of Truth with Analyste

Annalise Ashdown Lee is the head of business intelligence at Analyste, where her team helps startups distill and manage their data, so they can focus on what really matters: growth.

Prior to Analyste, Annalise worked in operations across a range of industries spanning apparel, beauty, and health. The Tydo team caught up with Annalise to discuss data pipelines, how she builds custom dashboards, and why brands should work from a single source of truth. 

Distilling Data Into Dashboards 

At Analyste, every client has a different set of needs and a different set of key questions. To dig into those questions, Annalise leverages custom-built dashboards using Tydo’s platform.

Most of her clients are interested in retention dashboards and cohorts. After looking at cohort data, they typically ask questions that focus on when customers are coming back and what they’re purchasing across multiple revenue events within a time window.

With cohort analyses, Annalise works directly with clients to define the parameters of each cohort, whether it’s month over month or specific batches of time corresponding to product drops. 

When onboarding new clients, the goal is to set up automated dashboards that deliver actionable insights in real time. But, Annalise notes that the first step is always understanding their questions and pain points on a day to day and week to week cadence. Then, she’ll dive deeper.

“Each client is inherently different. They ask their own set of unique questions, and they hone in on unique metrics. Using Tydo, we can deliver custom solutions.”

Designing Streamlined Pipelines

When Annalise first starts working with a DTC brand, she finds that most of them ask two questions: where’s our data going, and who has access to that data? 

As it relates to the data movement and storage pipelines, Annalise explains that while data sets permanently live in Shopify, she links Shopify to a secure warehouse via end-to-end encryption,  where data can be safely queried and analyzed. 

Then, after understanding the client’s questions, bottlenecks, and ongoing pain points, she determines what sales and demand dashboards already exist and then designs a streamlined, custom solution—created to save a client time and introduce accuracy and consistency into their reporting. 

When it comes to forecasting, Annalise’s approach focuses on mapping the forecast and the calculations that go into it to the brand’s real-time thought process. She adds that the rationale behind forecasting can be quite variable, thus the need for clear and concise mapping.

For example, a client might be focused on optimizing for a retail partnership, looking at a product with strong seasonality, or managing cash. In her words, these use cases all require different calculations and recommendations that are then distilled into custom dashboards.

“Data is often a foreign language to folks. It takes work to get brands on board, but once they get up to speed, they’ll see that their data is extremely powerful.”

Constructing a Single Source of Truth 

Annalise and her team partner with early-stage brands who don’t have full-time data hires, but they do have seemingly endless data needs. With all her clients, she stresses the importance of keeping Shopify clean from an accuracy and security perspective.

If data is changed or handled too much, human error can easily be introduced. And, that only makes analytics more complicated, more expensive, and less accurate. That’s why Annalise recommends working from a single source of truth, in her case leveraging Tydo.

She points out that there’s often a significant need for accuracy and specificity around inventory recommendations because it’s extremely costly to get that wrong. In addition, workforces are increasingly distributed and agile, so teams really do need to be aligned around the same data.

For emerging brands looking to upgrade their data ops, using an Analyste dashboard is faster than starting from scratch with any spreadsheet tool out there. Annalise creates a set of rules so that the data gets cleaned through the same process every time. Put simply, her work drastically reduces the margin of error for emerging brands.

“We start by identifying and isolating our clients’ pain points. Then, we get everyone on the same page by working from a single source of truth.”

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