Today’s modern reps move to new companies and roles every few years (or less). With this ever-shrinking sales talent lifecycle, enablement feels increased pressure to maximize productivity. That means finding better ways to focus and deliver readiness efforts (like training or coaching) when, where and how the sales force works.
This blog post was originially published by Rekener, now a Brainshark company.
Modern sales managers need comprehensive sales rep data to succeed. The HubSpot CRM is gaining traction because sales reps find it easier to input activity data. And there's important data in your cadence tool, the call recording system, your sales enablement platform and various spreadsheets. You may be thinking about building a data warehouse to pull all this data together. Before you build your own, read this post.
In this post, we'll cover three things.
- Why you need a data warehouse for your HubSpot CRM data;
- Why you shouldn't build it yourself; and
- How you can build your data warehouse in 10 minutes.
Why You Need a Data Warehouse for Your HubSpot CRM Data
Here are the top three reasons why you need a data warehouse for your HubSpot CRM data.
- Advanced cross object reporting
- Integrating data from multiple sources
- Visualizing trends and anomalies
Advanced cross object reporting. Your HubSpot CRM has sales rep data in different data objects. Our data shows that sales managers track seven or more metrics per sales rep. Cross object reporting is needed in order to roll up data from different objects at the sales rep level. By combining reps into teams, you can also compare one sales team to another.
HubSpot's advanced reporting includes only basic cross object reporting. A data warehouse can be used to transform data from different objects so it can be rolled up to the sales rep level. This lets you see the whole lifecycle of each rep's sales activity, from how they convert leads, all the way through pipeline generation and closing deals.
Cross object reporting of sales rep data in HubSpot CRM
Integrating data from multiple sources. Many companies keep quotas and sales targets in Google Sheets. We've also seen an increasing number of customers who rely on data in different systems. Sales cadence tools such as SalesLoft, Yesware and Outreach are great sources of data about email outreach. Call recording systems like Gong and Chorus are generating data about the quality of phone calls. And sales enablement systems like Seismic and MindTickle have valuable information about sales training.
You can use a data warehouse to integrate data from all these sources. Joining the data and rolling it up to the sales rep level produces a comprehensive view of each sales rep.
Visualizing trends and anomalies. Sales managers need to see how sales reps perform over time. This is particularly important for ramping up new sales reps.
With a data warehouse, metrics can be seen over time. Managers can see trends and identify when a key metric is off. This is particularly clear when performance data is compared to goals and targets.
Why You Shouldn't Built It Yourself
Don't do it yourself. There are three big reasons:
- Total cost of ownership is high
- There are no pre-built applications
- Business analysts don't always have enough domain expertise
High cost of ownership. The cost of business intelligence (BI) software is just the tip of the iceberg when it comes to building your own data warehouse. You need to factor in the cost of the cloud data platform and the integration of data sources. You'll need IT people to help with all this.
Once you have the data in the cloud, you'll need a team of SQL engineers. The SQL team joins the data and set up the tables for analysis. The top of the iceberg are the graphs and charts that sales managers need.
When you put it all together, the total cost of ownership is very high. The total cost of ownership for a BI solution can be well over $100,000 - $200,000 per year. And it takes a long time to deliver. Very often, it takes 9 months to a year to fully implement everything needed to build this yourself - hiring the team, setting up a data warehouse, doing ETL into the warehouse, organizing and cleaning the data, and putting a BI tool on top. Only then are you ready to start doing analysis.
No pre-built applications. The ads for BI tools make it look like they include sales analytics applications. The reality is that the BI tools can be used to build sales analytics. You need a team of SQL engineers to build the applications. This requires them to first understand the data structure, then join the data properly, and then build reports with the data.
Business analysts without domain expertise. If you have business analysts who do not come from a sales background, then sales managers need to be able to clearly define what they need. The likelihood that requirements get lost in translation is very high. It's all too common that we hear complaints from sales leaders that they have been asking for the same report from the BI team for months, but they are just one ticket in a large queue.
How Sales Scorecards Can Help
With sales scorecards, you can automatically set up a cloud-based data warehouse for customers. The integration with HubSpot CRM is pre-built, so it only takes a couple minutes to set up a comprehensive sales management platform that uses data from HubSpot CRM and other connected data sources.
On top of that, scorecards have multiple advantages over a do-it-yourself approach, including advanced cross-object reporting, integrated data from multiple sources, and data visualization over time. Best of all, they are pre-built and designed for sales managers.
Rekener (now Brainshark) is the fastest and most effective way to give your sales team powerful sales analytics. Contact our team today so we can crunch the data, while you focus on crushing your numbers.