How Renew is scaling self-serve analytics with Secoda AI

Renew is the AI-powered resident retention platform redefining the renewal moment, turning every lease decision into a revenue opportunity.

Behind this platform is a data team that powers revenue-driving initiatives like the Momentum Score, which predicts renewal likelihood and helps property managers focus retention efforts where they'll have the most impact. The team also manages performance reporting, preparing quarterly business reviews for partner communities and turning complex engagement data into clear insights on renewal rates, vacancy loss, and overall financial performance.

But even with strong analytics capabilities, the team faced a challenge with data accessibility across the business. Exploring their data and answering questions was painful. Getting answers to simple questions from Domo, their BI tool, meant logging in, finding the right dashboard, applying filters, and knowing which tables to use. This was a cumbersome process that could take 10-30 minutes for simple questions. For business users who weren’t familiar with Renew’s data structure, navigating it was overwhelming. Without clear context on which tables held the right data or which filters to use, many stopped trying altogether. What was needed was a conversational interface that could bypass all this complexity by understanding natural language questions, automatically querying the right tables with proper permissions, and delivering answers in seconds instead of minutes.

With Secoda AI connected to Slack, business users finally have an easy way to get answers. Today, every team that needs data asks questions directly in Slack. 

“It’s quickly become one of our most-used data tools. The level of engagement across our team has skyrocketed, and now there’s a constant stream of questions and insights flowing through Slack.” -  Suzie Carlson, Senior Analytics Engineer at Renew

Transforming how the team engages with data

Behind the scenes, Suzie and the analytics team connected Renew’s trusted data sources into Secoda, and the Slack integration brings Secoda AI directly into the workspace. When a user asks a question in their Slack channel, the Secoda AI chatbot replies in the thread with the result.

At first, the questions were straightforward: “How many units do we have at this property?” “What are the property names and locations for this partner?” “Can you summarize performance through June?” The speed of the responses encouraged more use, and soon sales teams were pulling property-level and partner-specific data on their own. One sales rep even built a partner-facing report directly from Secoda queries, documenting faster lease renewals, reduced vacancy loss by 5 days, and approximately $1.9 million in annual revenue impact at a 40% turn rate.

As usage grew, Suzie monitored the Slack channel to check accuracy and consistency. This oversight helped establish trust, and what started as a new tool quickly became part of daily routines. The outcome is clear: Renew moved from almost no data engagement to consistent, organization-wide reliance on Secoda AI in Slack.

According to Suzie, "Out of the business users that need data, 100% of them have engaged with Secoda."

Agents in practice

One of the biggest unlocks for Renew has been through deploying Agents. Agents are automated workflows that take the prompts you’d normally ask Secoda AI and run them on a schedule, surfacing results without anyone needing to remember to pull the data.

They have implemented several use cases:

1. Keeping momentum scores fresh

Renew's engineering team created a Momentum Score to predict whether residents are likely to renew based on internal behavioral signals and engagement patterns. The goal was to identify which residents would use the app to make renewal decisions.

To build the model, they asked Secoda AI to analyze these engagement signals and recommend optimal weights for each action. How much should an account login count compared to an email open? What weight should marketplace browsing carry? They took Secoda's recommendations and implemented the weighted scoring system directly into Renew's app.

Before Secoda Agents, updating these weights as new data came in was a manual, time-consuming process. Now, the engineering team has set up an Agent with the same prompt to run automatically every month. As resident behavior patterns evolve and more data accumulates, the Agent recalculates the optimal weights and keeps the Momentum Score accurate and current. What once required manual intervention now happens on autopilot, ensuring the predictive model always reflects the latest trends in resident engagement.

2. Automating daily metrics

Every morning, the team wants to know key operational numbers: how many new users were created yesterday, how many offers went out, how many renewal decisions happened, and whether those decisions were made in-app, marked as interested, or declined. These daily metrics help the team stay on top of platform activity and catch any unusual patterns quickly.

Before Secoda Agents, getting these numbers into Slack required a complicated workaround through Domo. Suzie had to maintain a daily metrics dataset, configure Domo to trigger an alert whenever that dataset updated, then write custom formulas to pull the metric names and values in the right format. It was functional, but cumbersome to set up and maintain.

Now, Suzie has set up a Secoda Agent that handles the entire workflow. She gave it a simple prompt asking what metrics are in the daily dataset and requesting the output in a clean date-metric-value format. The Agent runs automatically and delivers the formatted results directly into Slack, right where the team is already working. The goal is a completely seamless morning briefing that requires zero manual intervention.

3. Simplifying quarterly reviews

Quarterly business reviews are a critical touchpoint with partner communities, but preparing them has historically been a drain on time and resources. The process typically took around three days and involved multiple team members manually pulling data from various sources. Teams would reach out to Suzie asking if certain metrics existed in a table somewhere, then export that data into Google Sheets to build bar charts and other visualizations. They often bypassed Domo entirely, preferring the flexibility of spreadsheets despite the manual effort required.

The challenge wasn't just the time investment but the repetition. Each quarter, they were essentially running the same analysis: comparing performance metrics from one period to the next, identifying trends, and surfacing notable changes. It was the same data over and over, just refreshed with new numbers.

Now, Renew is using Secoda Agents to transform this workflow. Instead of manually reconstructing the same analysis each quarter, they're setting up Agents with prompts like "Compare last quarter to this quarter and surface the biggest changes in key metrics" or "What are some of the insights you can pull out of this data between Q2 and Q3?" The Agent can run the same analysis consistently, ensuring nothing gets missed while dramatically reducing prep time. What once required three days of collaborative manual work can now be generated automatically, freeing the team to focus on interpreting the results and building strategic recommendations rather than wrestling with data extraction. 

Takeaway

Renew has gone from limited data engagement outside technical teams to full adoption among business users. By embedding Secoda AI into Slack, they’ve made self-serve analytics part of everyone’s workflow. Sales teams are delivering stronger partner reports, daily metrics are automated, and projects like the Momentum Score are maintained with less manual work.

Secoda has become Renew’s most widely used data tool, and one that is already creating measurable value across their business.