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How to accelerate your business growth using data analytics

Learn how data analytics can help you supercharge your business growth by tracking KPIs and discovering insights.

How To
March 4, 2020
How to accelerate your business growth using data analytics
Learn how data analytics can help you supercharge your business growth by tracking KPIs and discovering insights.

Raise your hand if you’ve ever heard that “data-driven companies make more money”.

McKinsey started beating that drum half a decade ago. Financial Times wrote extensively about the topic. Google even commissioned a multi-year study from Boston Consulting Group (BCG), which showed that “best-in-class digital marketers benefit from 1.4 times greater cost benefits and up to 2.5 times revenue impact” after implementing analytics to drive their business growth.

But what they usually fail to tell you is how to use your data to make that sweet dough.

In this article, we’ll break it down for you: a guide on how to use analytics to help your business grow faster.

1) Keep a finger on the pulse of your KPIs

How much water can a boat take in before sinking? Hard to tell, of course. Depends on multiple factors: the size of the boat, what it’s made off, whether or not the water can be pumped out to help it stay afloat … but one thing we can all agree on is that letting the water into the boat in the first place would be ill-advised.

If you were the captain of your boat, would you trust your sailor’s gut feelings about how much water was on board, or would you demand someone to check under the deck? Aye, aye, Captain, the report is on its way. It’s surprising, then, that almost half of companies base their decisions on gut feeling instead of data.

So, the first area in which analytics can help is by using data to track key performance indicators (KPIs) for your company. Having KPIs in place allows you to quickly answer these questions:

  • How much revenue was generated this week? (KPI: weekly revenue)
  • Did you make a profit or loss? (KPI: profit margin)
  • Are the costs of acquiring a new customer going up or down? (KPI: customer acquisition cost)
  • How many customers’ orders can we fulfill before we need to reorder from our suppliers? (KPI: units on stock)
  • How long will it take to close that big enterprise client? (KPI: sales cycle duration)

KPIs help you keep a finger on the pulse of your business. Knowing your KPIs means you can sieve through the superficial vanity metrics and look at your performance objectively.

What if you acquired 100 new customers today? If that cost you $10k but none of the customers sign up after their trial expires, you just made a bad business decision. Without tracking KPIs, you might not even be aware of it.

Insider tip: Keboola integrates with any visualization tool to give you a one-click deployment for all of your KPI dashboarding needs.

2) Predict future demand (and supply)

Knowing when customers are likely to order from you (and how much) is the difference between servicing your customers or leaving money on the table. Hey, if you fail to fulfill your customers’ needs, your competitors will be more than happy to.

Companies which do not use analytics to predict demand (or supply) often fall prey to the following errors:

  • Customers order, but you have no product in stock to meet their needs.
  • Customers order, but you are too late at getting your product from your own suppliers, so your customers become unhappy with delivery times and begin canceling orders.
  • You think customers will order, so you stock in bulk, but no one does. Now you are left with a lot of stock and no one to take it off your hands.

Even if you trade in digital products or offer services, the same logic applies:

  • Are you leaving money on the table because you wrongfully predicted how many server nodes your website would need to handle increased traffic spurs?
  • Are you growing exponentially, but are unable to sign up new clients to your consulting because you failed to train account managers on time?

Insider tip: Keboola automates your data engineering to get your data-stack ready for predictive analytics in just a couple of clicks.

3) Build better products with machine learning

With the advent of machine learning and artificial intelligence, the hyper-growing startups have gained an advantage over their competitors. Netflix uses a recommender system to build personal recommendations based on past-viewing data. Airbnb uses graph infrastructure to tailor its offerings to each traveler.

Both companies are renowned not only for succeeding in their respective high-competitive industries, but also for crushing their competition with their superior product offering.

Relying on cutting edge machine learning is not the only way to build a better product. Industry veterans are heavily relying on customer research to understand what the next “hot thing” is going to be. Frozen yogurt? Kombucha? Pea tea?

Even if you’re not dabbling in the dark arts of advanced AI, analytics can help you build better products as well.

A common example is to have your customers help you prioritize customer development. Listen to what they like or dislike about your product and adjust your roadmap accordingly.

Here are a couple of ways in which strong brands utilize customer feedback:

  • Scrap the web and social media for your customers’ comments and reviews. Use NLP to categorize them and determine what they like or dislike.
  • Survey customers at multiple touchpoints during their customer journey (pre-purchase, post-purchase, etc.).
  • Create a customer-facing feature development roadmap, where your customers can vote on the features that they want to be released first.

Insider tip: Keboola automates the NLP machine learning behind text-review categorization. This gives you more time to obtain insights into your product development.

4) Know your customer

In the era of hyper-personalization, your customers expect you to tailor your products and services to a market of one (aka, them).

The principle is simple. Unless you break down your customer needs into micro-segments, your product offerings are not going to make much sense to the end-user.

Imagine you are selling beverages. One of your segments is crazy about piping hot matcha tea, while another goes nuts for chilled iced tea. If you compromise and split it down the middle by offering them lukewarm tea, neither of the segments is going to be very happy.

To dig even deeper into the subject, the ultimate segmentation is personalization. At a time when companies collect a lot of data about their customers (CRM contacts, financial information, support ticketing, social media…), it is crazy that we’re not using this data for personalized offerings.

Insider tip: Keboola scaffolds automate the extraction of customer support, CRM, and financial customer data, bringing you up to speed with the engineering stack needed for segmentation and personalization.

Where to take it from here?

Knowing how to use analytics to accelerate your growth is often not enough.

There are also people, processes and organizational specifics that can make the difference between deploying analytics to your advantage, or sinking into analysis paralysis.

Make sure to delve deeper into how to build a data-driven company culture - an exploration of the factors that set apart the most successful fast-growing companies from their peers.

#getsmarter
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