5 Monster Spreadsheets You Can Automate With Rekener

5 Monster Spreadsheets You Can Automate With Rekener

Spreadsheets Are Awesome

Spreadsheets are alive and well in B2B sales, marketing and operations.  Put simply, they are great for intellectual analysis. Pivot tables and VLOOKUPs are amazing for slicing customer data in multiple dimensions to get a better understanding of who customers are, what they tend to buy and how they use different products and services.

Except When They Aren't Awesome

As great as spreadsheets can be for generating intellectual insights using customer data, there are at least four big reasons why they are not the best solution: 

  1. Joining data from the CRM, marketing automation platform, usage tracking systems and customer support tools can be really difficult. 
  2. Spreadsheets take a lot of time to maintain.  Source data needs to be refreshed and the analysis updated with every new month, quarter or year. 
  3. Some spreadsheets get so big that only one person really knows how they work. It's not good when a single person with a monster spreadsheet creates a throttle on your business. 
  4. There is no good mechanism for translating the insights in your spreadsheet analysis to actual execution on the sales floor, with the marketing team or with your product managers. 

So, what are the alternatives?

Building Your Own Data Warehouse Will Cost You

For businesses with enough resources, the alternative to monster spreadsheets is to cobble together a business intelligence platform.  This is a big investment in technology, team and time.  You need to stand up a data warehouse and build integrations for your data sources.  You need database admins to set up and maintain a data structure.  You need SQL engineers to build the tables that feed useful reports.  On top of it all, you need a BI platform with good visualizations for all those reports.

The positive of a business intelligence platform is that the integrations and reports only need to be built once and then are updated automatically.  This overcomes the first two limits of spreadsheets listed above.  But there are two big negatives (beyond the initial cash outlay in technology to get started).  First, more reports require more analysts.  This scales better than spreadsheets, but human resources are still a limiting factor, and humans are expensive.  Second, like spreadsheets, there still is no connection between the insights generated by all those reports and the execution of strategy based on those insights. 

Rekener Gets It Done With Automation

Rekener represents a new breed of B2B data platform. Rekener leverages customer data to do all the intellectual work that can be done in spreadsheets or SQL but without the limitations on scale.  Rekener starts by creating a cloud-based data warehouse with a data structure that automatically overcomes the limitations of the Salesforce CRM.  Then, Rekener creates a 360 degree view of the customer that is automatically maintained. 

From there, the Rekener Platform uses dynamic metrics and tables to build analytical applications that automate those monster spreadsheets.  The insights from Rekener applications can be used to not only develop go-to-market strategies, but also to execute those strategies as part of your sales and marketing process.  My colleague Greg Keshian described a great example of this in his blog post on "Feeding a Sales Cadence Tool to Destroy Your Net New Number."

5 Monster Spreadsheets That Rekener Customers are Automating

Sales Performance Scorecards

Sales managers at all levels depend on metrics to track performance of teams and reps.  Salesforce reports provide some visibility into how teams and reps are performing with respect to individual metrics, but they don't provide a rollup of key metrics at the team or rep level.  As a result, managers end up spending weekend or evening time pulling data into spreadsheets, or they have analysts prepare spreadsheets for them.  This doesn't provide near real-time data, and it doesn't scale as the team grows.

Rekener automates sales rep reporting.  The Rekener Platform is able to slice account level data by sales team or sales rep and shows up-to-date metrics.  Importantly, the metrics can be fully customized.  Here is a screen shot of a sales team broken down at the BDR level.

Sales rep scorecard

One of the big limitations of Salesforce reporting is the inability to see data over time.  Rekener adds the time dimension.  This makes it possible to see how performance is trending over time.

Inside sales rep metrics over time

Territory and Account Drilldowns

Sales managers also need visibility into their accounts, rolled up by territory.  This is another set of monster speadsheets that are often done in Excel or Google Sheets and updated monthly or even quarterly.  By comparison, Rekener accounts can be grouped according to territories, and metrics can be dynamically applied to all of the territories and updated automatically.

Here is an example of a drill down of a territory comprised of Enterprise accounts

Territory analysis

Segmentation Based on Super Metrics

Sales and marketing teams perform segmentation analysis to understand the attributes of good customers.  The definition of "good" depends on which metric you're trying to optimize.  For example, companies will often optimize segments based on net new bookings.

Several of Rekener's customers are optimizing segments based on super metrics, which are multiple metrics combined into one.  A good example of a super metric is Lifetime Value (LTV).  For recurring revenue businesses, LTV is the average revenue per customer multiplied by the customer lifetime.  The customer lifetime is usually calculated as the inverse of 1 minus the renewal rate.

It's difficult to generate reports based on super metrics in Salesforce.  So, many companies do the analysis in a monster spreadsheet.  By comparison, in Rekener, super metrics are easy to create and can be used dynamically for any data set.  Here's an example of a segmentation analysis to optimize for LTV per new customer.

Segmentation analysis

Sales Velocity Calculations

Sales velocity is another super metric.  It's equal to the value per opportunity multiplied by the number of opportunities, all divided by the length of the sales cycle.  To learn more about Sales Velocity, check out Greg Keshian's "7 Thoughts About Sales Velocity."

Calculating sales velocity in spreadsheets is tough, especially if you want to see how sales velocity is trending over time.  In Rekener, it's easy to create the sales velocity metric, and then it can be used to analyze any data set over any time period.

Here is an example of sales velocity calculations for new business, by month.

Sales velocity

ARR Waterfalls for Better Forecasting

Historical pipeline analysis can help your forecasting for future periods.  To do it right, you need to cohort opportunities based on attributes such as when they were created.  Then, you can analyze each cohort to assess pipeline won, lost and still open at the end of each subsequent period.  Doing this in spreadsheets is an overwhelming task, but in Rekener it can be fully automated.

Opportunity cohort analysis

 

Conclusions

If your business is building or maintaining a monster spreadsheet for one of these applications or for something else, think about whether or not you're making best use of your time.  With a modern customer data platform such as Rekener, it's possible to use dynamic metrics and tables to automate monster spreadsheets.  This will free up "headspace" for your valuable analysts and ops people to focus on improving business strategy and go-to-market operations.  And your sales, marketing, finance and product leaders will be much happier because they will have the data that they need at their fingertips.

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Alex Laats

Alex is CEO and Founder of Rekener. Previously, he served as President and Chief Operating Officer at ZeroTurnaround and as President of the Delta Division of BBN Technologies. At BBN, Alex co-founded RAMP and AVOKE, both recurring SaaS businesses. Alex’s companies have generated $500M in liquidity events and more than $1B in sales. He’s been working on cracking the code on recurring revenue businesses since 1999 when he started an application service provider (remember those?) called Informio.

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