How to Create A Reliable Business Intelligence Strategy: AppSumo’s Head of Business Intelligence Explains

Creating a solid business intelligence strategy is key to getting clear, actionable insights that drive your business forward.

With a strong BI strategy in place, you’ll be better equipped to answer important questions impacting your business goals.

“What’s causing an uptick in refunds from new buyers after sales events?”

“Which marketing channels attract repeat buyers, and how should we reallocate spend?”

“How many emails are too many emails for our top purchasers?”

But without a BI strategy, you're basically flying blind.

Instead of making data-driven decisions, you'll end up chucking random darts at the market, thinking to yourself: “I don’t know. I’m making this up as I go.” 

And that’s no way to do business.

What is a business intelligence strategy?

Business intelligence goes by many names, like data analysis and data reporting. Whatever you call it, the goals are always the same:

• Deep dive into all your data sources
• Uncover new opportunities to meet KPIs
• Construct a reliable data story that better informs business decisions

Business intelligence is NOT throwing cryptic reports at your team, expecting them to make sense of the numbers. A successful BI strategy helps everyone understand the playbook—even if they’re working on different pages.

Can your business operate without a BI strategy?

Technically, yes. Just don’t expect your business processes to be streamlined.

Before our fearless Head of BI, Bob Nathe, took the helm, AppSumo’s data scene operated like the Wild West. (His words, not ours.)

We had different teams tracking different datasets across different tools, completely disconnected from a single source of truth. Some teams relied on daily reports; others needed hourly updates. Either way, the numbers didn’t always align, which left more room for debating than decision-making. Was there any correlation between deal-level performance, session data, and paid metrics? Maybe.

But without a reliable way to cleanse and standardize the data, report consistently, and build out dashboards—our questions largely remained unanswered.

So our two-man BI team did what they do best: they helped AppSumo create a business intelligence strategy. And now we’re spilling the beans.

AppSumo’s 6-step guide to creating a business intelligence strategy

Step 1: Evaluate your current data infrastructure

You need to know where your data’s generated, how it’s generated, and which team members are in charge of leveraging it.

If you think your company’s too small for this step, think again!

Even on a liquid-thin budget with limited resources, you can build a solid data foundation using Google Sheets. On top of connecting datasets and creating dashboards, this budget-friendly tool allows you to set up automations. You can even use Zapier to connect multiple systems and send all that data back to Google Sheets. Automate as much as possible. Consistency is the best way to capture reliable and trustworthy data.

Above all else, be data curious. Channel your inner Pac-Man and chase down every data point you can. The golden nuggets are out there if you keep digging.

Step 2: Establish your BI team

The right people (or person) will be responsible for your business data so don’t gloss over this step.

Your BI team will be responsible for:

• Developing data policies for collecting, storing, processing, and disposing data
• Complying with the standards set by stakeholders and other third parties
• Improving data quality and maintaining consistency
• Enforcing day-to-day procedures for data governance

Step 3: Data management and preparation

Standardizing all your data is where the rubber meets the road. For AppSumo’s BI team, this all happens in a cloud-based data warehouse called Snowflake.

This BI platform allows us to manipulate, organize, cleanse, and derive all of our standard reporting and analytics. (But this isn’t an ad for Snowflake.)

If you’re just starting out, you can find several low-cost tools—like Google Sheets and Zapier—to get you up and running. You could also use a tool like Boost.space to consolidate, organize, and sync data from over 2,000 apps, including CRMs, ecommerce platforms, and BI tools.

From there, you can simply start asking questions. And we recommend you do so! Our BI experts approach data on a grain level by asking themselves:

1. How can you build reliable and reusable data?
2. What is the most basic record you can find in a table?
3. How many ways can you slice and dice the data?
4. Are there new dimensions to the data?
5. Are there new opportunities to support business needs?

They spend most of their days writing SQL code to answer these questions. Very glamorous, we know.

Step 4: Pick your data visualization platform

AppSumo uses Snowflake for data management, as well as Google Sheets and Looker Studio for dashboarding. (We’re also testing Tableau right now.)

However, the most important thing to consider when choosing a visualization platform is your audience.

Are they power users who prefer good old-fashioned tables? Or do they want charts and graphs that are easy to digest at a glance?

Carefully consider their needs and limitations because pulling the numbers is only half the job.

Step 5: Tell a story with data analytics

The other half is crafting a story that bridges the gap between what you learned and what you know.

Your BI team will need to connect ideas, share rich insights, and provide enough context to help team members leverage findings.

In the end, the data story should help answer the age-old question: “So how’s the business doing?”

Step 6: Develop your BI roadmap (and pitfalls to avoid)

Your organization will constantly face unforeseen challenges, which means your business intelligence strategy needs to be a long game.

BI roadmaps focus on business goals and visualize target KPIs, important milestones, and specific BI goals. Developing your BI roadmap is key to optimizing and overcoming obstacles as holistically as possible. In other words, your roadmap helps you adapt and stay nimble.

So it’s critical that you avoid these two common pitfalls before building out your BI roadmap.

Misalignment with business goals

There’s nothing intelligent about a business intelligence strategy that doesn’t align with your business goals. Your BI team needs to understand where you’d like to go, so they can help you get there. Otherwise, they’ll be pulling threads, KPIs, and metrics that lead you nowhere—wasting valuable time and resources along the way.

Lacking a data-driven culture

Everyone in your organization needs to believe that data can accelerate business growth. Without that, most of your data-driven initiatives will fail. It’ll take some time to find value in your data, but stay the course! As the data becomes more trustworthy, you’ll be able to turn new insights into strategic business decisions.

Now let’s talk about something everyone wants to incorporate into their business intelligence strategy.

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Prescriptive analytics

How can we use the data we have to be prescriptive with BI solutions?

That’s a question Bob’s been asking for the past three years. He was so curious that he built a customer segmentation using AppSumo’s data to understand our buyer behavior in more depth. Which is only now seeing traction in the last six weeks. Was that wasted energy or effort? Not according to Bob—it’s just deferred.

It’s easy to see a data trend and then get prescriptive. But it’s difficult to go from disorganized analytics to prescriptive analytics without an open checkbook.

Don’t jump the gun before you’ve got the time, resources, and manpower to back you up. Sometimes the only thing you learn from failure is to slow down.

So is there business value in a clear BI strategy?

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There’s literally nothing but value!

Your BI team can take complex data and provide a window into what’s working or not, helping you make data-backed decisions using trustworthy information.

At the end of the day, a business intelligence strategy offers unique insights that can help your entire organization succeed together.

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