If you’re in a marketing or revenue-focused role, chances are that at some point you’ve faced frustrations with your data and reporting tools.
Developing clear-cut reporting and insight across a complex organization can be a time-consuming process, riddled with data “silos” created by separate non-integrated platforms.
For many organizations, this challenge can lead to frustration across the business. We’ve worked with many organizations in which marketing and sales stakeholders have struggled to make effective business cases to leadership for increasing their investment in analytics, even as they routinely drop everything to support intensive reporting sprints to cobble together data and insight in time for QBRs, board meetings, and other key milestones.
While these challenges are commonplace, they are not insurmountable. In fact, in our experience working with hundreds of high-growth companies, we have observed that the most successful apply three relatively simple concepts to help drive a more data-driven and effective reporting culture. Taken collectively, these three approaches help create a virtuous cycle in which trustworthy reports fuel better business performance, which fuels increased investment in growth technologies and reporting infrastructure.
Here are the three fundamental reporting best practices behind today’s most successful high-growth companies:
The classic pitfall of today’s tech stacks is that they are “connected” but not integrated. This means that they are functional, but they don’t aggregate data in the same way. Dubbed “frankensystems” by Dharmesh Shah at INBOUND 2021, these cobbled-together systems are familiar to most marketers.
Businesses no longer need to accept this. While it may take time and resources to fully divest of a “frankensystem,” a good first step is to align on a single source of truth for prospect and customer data, and uniform definitions for prospect and customer lifecycle stages.
Whether you’ve invested in a BI tool, rely on a platform like HubSpot, or even manage reporting inside a series of excel spreadsheets, you need to make sure you have a method for extracting insight from data and alignment across all revenue stakeholders on marketing lifecycle stages, deal stages, ideal customer profiles, and KPIs.
It’s important in this situation to think of a data collection tool like a car. The car itself has value and serves a purpose, but it’s not valuable in a silo. It needs oil, maintenance, and inspections to keep it road-safe, and, like a car, your data collection and reporting tools need the same kind of support.
Your company made an investment in that resource, whether you subscribe on a monthly basis, through an annual contract, or maybe even you bought a platform license - regardless, you made an investment in the ability to collect data. Without the ability to extract insight from that data - whether you need additional tech to refine reporting, or a consultative partner to help extract insight from it - the investment loses value, making that investment by your company effectively less meaningful. On top of that, any further investment your company makes in that tool only furthers a potential sunken cost. You made this investment because it’s important to your company to be able to collect and analyze data - that importance hasn’t diminished. You simply need an additional tool or resource to make it properly functional.
Data without analysis is just numbers. Much like a collection of raw ingredients requires food to become a meal, so does data require a vehicle for evaluation. Let’s take a practical example. You may know the number of leads your company has generated in the last year. Your head of marketing may know how many marketing qualified leads came from that pool, and the head of sales or revenue may know the number of sales qualified leads or opportunities that came from those. Disparately, these are just numbers. When collected and analyzed together, they can give you a sense of your funnel conversion rates, from the first interest a prospect takes in your brand, to your ability to qualify that prospect’s interest and fit, to your sales team’s ability to create a viable potential sale.
You may already be thinking “well I know my company’s funnel conversion rates” and that’s a pretty common starting point. I would begin by asking what you don’t know. For example, if you know your company’s funnel conversion rates, do you know your funnel conversion rates based on specific audience pools, such as within specific industries or different company profiles? Do you know how commonly you see one persona versus another? More importantly, do you integrate your “funnel” data with customer success metrics like LTV, expansion rates, churn rates, and upgrade/downgrade trends?
The more granular of a look you can take into your data, and the more closely you can examine that insight, the more impactful takeaways you’ll be able to generate for your company’s growth. Why? Because the closer you look at the data, the more closely you are looking at your customers – the real people and businesses who you are serving.
Viewing your data in these terms, and thinking beyond conversion rates to focus on real-world business contexts, helps marketers and sales leaders frame a better strategy.
All of what we’ve said above may feel invalidated if met by “that sounds like a nice to have, not a need to have” - a stance we hear commonly. When prioritizing, you may struggle to define the importance of making an investment into your reporting stack now versus in 6 months, or at the start of your next fiscal year.
We often think of reporting and growth as going hand in hand. If you can’t analyze your success in the market, you can’t adapt to it. So if you are facing pushback on the concept of making an investment into your report tech stack, you should address that by asking “how much longer can we afford to wait to grow?” Is your organization willing to remain at your current pace of revenue growth - whether you’re thinking about top, middle, or bottom of the funnel pipeline development - for that same period of time?
Top-performing organizations ask these questions, treating reporting as business-critical and, conversely, viewing poor reports as a business and revenue risk. Moreover, they invest both time and resources into optimizing their analytics and reporting approaches. This can include:
Takeaway
To accelerate growth, companies need to understand the hidden strategic opportunities within their prospect and customer bases. Traditional reporting and analytics often fall short, either because data is fragmented across systems or companies view data through “traditional” metrics that don’t yield transformative insight. To combat this, top-performing companies invest in one point of truth for data, focus on customer-centric insights, and treat their business intelligence strategies and partnerships as business-critical. Moreover, improvements in CRM reporting platforms and outsourced data science mean it is now possible to accomplish this three-pronged approach more cost-effectively than ever before.