How To Consolidate All Your Business Development Data For Instant Insights
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Your company may have great business development tools, but that doesn’t mean the tools provide great insights. Sure, these tools have reports. For example, Outreach offers a breakdown of representative activity, and Salesforce shows how opportunities are progressing. However, being siloed within these platforms limits your analysis. Combined, these data points could create a comprehensive picture of business performance and highlight potential challenges.
But first, how do you bring these data points together?
The old way: Pulling data from source systems
The process of manually extracting and consolidating meaningful intelligence from the array of disconnected tools used by Business Development Representative (BDR) teams has become an immensely time-consuming and complex undertaking, draining valuable resources and delaying critical decision-making.
The time tax: Endless hours of manual data wrangling
Pulling data from disparate sources like Outreach, Gong, and CRM systems manually is an incredibly time-consuming process. Analysts and BD specialists often spend countless hours exporting, cleaning, and consolidating data into spreadsheets.
This labor-intensive work diverts valuable time away from strategic analysis and actionable insights. The sheer volume of data, coupled with the need to ensure accuracy, turns what should be a quick analysis into a multi-day ordeal, delaying business decisions.
The error epidemic: Manual data's inherent unreliability
Manual data manipulation is a breeding ground for errors. From simple typos to complex formula mistakes, the risk of inaccuracies is significant. When dealing with large datasets, even minor errors can propagate, leading to flawed reporting and misleading conclusions.
This compromises the integrity of the analysis and undermines confidence in data-driven decisions. Additionally, manual processes make it difficult to trace the origin of errors, hindering effective troubleshooting and data validation.
Fragmented data, fragmented understanding
Even if manual processes are executed flawlessly, the fundamental problem of siloed data remains. Each source system (Outreach, Gong, CRM) operates independently, creating isolated islands of information. This lack of a unified view prevents analysts from seeing the complete picture of BDR performance and customer interactions.
Without the ability to correlate data across systems, it's impossible to identify meaningful patterns, understand the full customer journey, or derive truly actionable insights. This fragmented understanding leads to incomplete analyses and missed opportunities for optimization.
To make better decisions faster, you should be working with cloud data that lives in one place: your warehouse. Fortunately, Sigma is the best platform for analyzing live cloud data.
The new way: Using Sigma to consolidate reporting across tools
At Sigma, our team of analytics engineers developed our BDR Operations workbook to consolidate reporting and enhance inspection.
In one space, we can perform analysis on:
- Conversion rates per sales stage
- Overall, manager-level, and rep-level quota pacing
- Efficiency of our organization and reps, even down to the activity type
With this approach, there’s no more Salesforce reporting sprawl. No more inconclusive comparisons between Outreach and Salesforce reports. Instead, we have a singular space to assess everything we need to manage, inspect, and coach our Business Development team.
How we built our BDR operations workbook
In order to consolidate reporting, we first needed to set up our models in Snowflake. We have four main models that power this workbook:
- Salesforce_opportunities
- Our opportunities: all stage changes, which rep booked the initial meeting, how the meeting was booked, etc.
- Outreach_activity
- All Outreach Activity from BDRs
- Outreach account ID linked to their Salesforce account ID
- Fivetran connection for near-time data
- BDR_quotas
- A Sigma Input Table for manual entry of our quotas. This allows us to add or update BDR quotas easily
- Fiscal_calendar
- Our model that shows which dates fall in which fiscal quarter (FQ)
Once set up in Snowflake, we can perform all of our aggregations and calculations inside of Sigma. We use fiscal_calendar to categorize all dates by FQ. Then, by using the name of the BDR, Salesforce Account ID, and FQ as keys, we can perform lookups to correlate all of this data.
This allows for near-time data on stage totals, current pacing, and our suite of conversion rates. With Sigma, we can quickly filter these metrics by one or many variables, such as individual rep, manager, date range, industry, activity type, etc.
Our conversion rates are not just limited to stage progression. We can assess every rep, on an individual level and team level, on how efficient they are in:
- Prospects Connected with to Meetings Booked
- Out of all prospects we actually positively connect with through Outreach, Nooks, etc., how many do we book a meeting with?
- Accounts Connected with to Meetings Booked
- Out of all accounts we actually positively connect with through Outreach, Nooks, etc., how many do we book a meeting with?
- Connected Calls to Meetings Booked
- Email Replies to Meetings Booked
We can also measure organizational, team, or individual production rates. We can break down these rates by date range, region, industry, customer verticals, etc. This can answer fascinating questions like, “What reps are most effective in calling in Industry A and Industry B?” We have the visibility to discover quantitative insights that can then be investigated qualitatively.
Every single tool in our Business Development tech stack now flows into this workbook. With Sigma’s bookmarks, users can bookmark filtering to have specific reports at hand quickly. It’s saved our team's time by eliminating reporting sprawl and allowing for unprecedented visibility.
Improving business team alignment and self-service
Sigma’s spreadsheet UI and underlying data features superpower this workbook’s usability. For our analytics engineering team, there are very few ad-hoc data requests because most questions posed by our Business Development team can be self-answered.
Don’t just take my word for it. My colleague Jimmy Chen, Senior Director of Sales Development at Sigma, says it’s completely transformed his relationship with data. “In prior organizations, I was left scrambling across multiple sources of data (Outreach, Salesforce, various tools), often with slightly different numbers.
Through Sigma, I can see everything through a single pane of glass and make in-line edits to SFDC and the CDW,” he says. “The BDR leadership at Sigma uses the workbooks to power everything from tracking performance indicators for coaching to doing deep analysis across territories. It's truly empowered our organization to run with data at the center.”
Sigma’s ability to show underlying data bolsters the impact of metrics such as our “Prospects Connected to Meetings Booked,” because this metric, in Sigma’s friendly spreadsheet UI, becomes much more than just a conversion rate. With just a few clicks, users can quickly answer questions about this metric, such as:
- What specific meetings were booked?
- What activities were completed that led to these meetings being booked?
- What type of activity actually booked the meeting?
- How many touchpoints occurred before the meeting was booked?
Not only does this empower our Business Development team, but Sigma enables true self-service, giving valuable time back to workbook users and the analytics engineering team.
From tool clutter to unified performance
Business development is as effective as it is efficient. Siloed data in source systems prevents the analysis necessary for truly understanding performance, and more importantly, efficiency.
A one-stop shop, powered by Sigma and a data warehouse, grants access to the analysis a business development organization needs in order to accessibly measure and monitor performance and efficiency. Check out our interactive demos to see how Sigma accomplishes these goals.
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