Decision Making Only As Good As Quality Of Data Studied

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Over the years, I have become somewhat of a “data hound”, looking for every morsel of wisdom I can get about my business, to help make smarter decisions. The good news here: data is king. You can’t effectively manage your business without it. But using accurate data is critical, and getting that is not always easy. And if you don’t have accurate data, you may be making the wrong business decisions that could end up hurting your business, when you thought you were helping it. Allow me to explain.

Case Study #1: Managing Sales Pipeline

In most B2B businesses that have a long sales cycle, the only way assess the effectiveness of your sales team and predict future revenues is based on data your sales team enters into your CRM. Here you would be looking to see a salesperson’s number of accounts growing, see how those leads are working their way through the sales funnel from qualified lead to closed sales and the total dollar value of the pipeline being managed.

But think about what I just said: you are valuing the success of your sales team based on the data that they themselves are entering (or not entering) in the CRM system. That creates multiple problems. First, I have seen situations where salespeople will actually enter false information, to make it look like their efforts are more successful than they really are, trying to save their jobs. And second, any time you are reliant on humans for data, there is plenty of room for error.

For example, did the salesperson remember to enter a new lead into the CRM? Did they remember to update the status of a lead (e.g., from active to dead)? Did they update the dollar value of that lead from $20,000 to $10,000 after they learned the client didn’t need as many products as they first thought? Did they update the expected close date from April to June, after they learned the project has been delayed? You get the point. Most businesses are making mission critical decisions based on future expected revenues from this data. And, more often than not, the data in the system is not very accurate, updated or reliable.

If your CRM suggests you are working with over $1,000,000 of potential leads, and your normal conversion rate is 20%. You would think there is a reasonable chance to close $200,000 in sales. Monies you would be running the business with and paying your bills and payroll. If that $200,000 doesn’t show up on time, as predicted, and you don’t have cash in the bank in reserve, bad data could put you in an illiquid position and potentially take you out of business.

So, when managing sales pipelines like this, you need to do to your best to scrub the data. Every week, remind your salespeople to update their data in the system for any changes? In your one-on-one meetings with the team, talk through their list, line by line, to ensure what the system data is telling you, is actually the reality. And where you can, build automated systems that updates data for any actions made (e.g., as new email leads come into business, they automatically get entered in CRM). This includes building in automated tasks and reminders for each lead, to make sure the leads are actually being moved forward and the salespeople are getting system-triggered actions they need to take for each lead. Most good CRMs or sales enablement tools can help you here.

Case Study #2: Managing Marketing Spend

The quality of your marketing efforts is also dependent on the quality of the data being managed and studied. Here are the two most-typical problems: (1) is your marketing team managing towards the right data metrics in the first place; and (2) is the appropriate credit being given to the marketing channel that actually drove the lead, in a multi-device world where getting the proper attribution is not always easy (e.g., first learned about you through Google paid advertising on their office PC, but came to you direct from the mobile phone where you lost the Google tracking).

Let me talk through a recent example I lived through. We recently hired an ad agency to manage our paid search campaign. We told them immediate return on ad spend (ROAS), defined as clearly attributed revenues from the campaign divided by marketing cost of campaign, as the key metric to drive. A strange thing started to happen in our business: our low ticket, online ecommerce transactions started to take off, but our desired high ticket, offline B2B transactions were not growing at all. By telling our agency to focus on “immediate” ROAS, the only way they could hit the desired target was by focusing on smaller orders that were immediately ready to book online. That excluded the desired longer sales cycle leads we really wanted to be growing.

So, after six months of these learnings, we switched directions. We told the agency immediate ROAS was no longer the goal. We would be happy waiting our three month sales cycle, before studying our ROAS. Instead, the leading indicator of future desired B2B sales, was immediate B2B leads that came in from that marketing effort. That would be the key metric to manage for. And, as soon as we made that change, our quick, low ticket sales started to fall back to more normal levels, and our desired B2B leads started to reach record heights. We were thrilled, thinking we had finally “cracked the code” to scaling our business.

But did we? A B2B lead is only valuable, if they ultimately convert into B2B transactions and revenues. So, in April, we did a retroactive cohort analysis of all B2B leads that came into the business in January (our normal three month booking window). And, what we learned was concerning: the B2B leads were coming into the business in record numbers, but very few of them were actually converting into sales, at levels far lower than our typical conversion rates. And after researching this further with our sales team, we learned the leads that were coming in, were very price sensitive, shopping many websites at once looking for the lowest price, and were often looking for last minute deliveries that were impossible to get the products to them in time.

So, now we are back to the drawing board, trying to figure out the right metric to be managing to? Or, if the same B2B lead metric, how to optimize the campaign trying to find leads we can actually work with. And, making sure we are giving proper attribution to all the leads coming into the business, to ensure we are not missing anything important in our look at the data. We also want to be careful not to “throw the baby out with the bath water”. Maybe there is something going on operationally, that is getting in the way of sales not converting, and the marketing agency is actually doing a great job. Time well tell.

Concluding Thoughts

So, any you can see, data is critical to managing your business. I gave you examples in sales and marketing. But, I easily could have given you data-driven examples in other areas of your business, like operations, finance, human resources or technology. So, make sure you are living in a world where data is king. But more importantly, accurate data is king with the business being driven by metrics that are the most important and reliable for predicting and driving future success and desired outcomes. The data is only as good as the effort you put into it!!

George Deeb is an entrepreneurial CEO, growth expert at Red Rocket Ventures, and author of “101 Startup Lessons—An Entrepreneur’s Handbook”.



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