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A Deep Dive into How Data Can Drive Startup Growth

Just like in any business sector, data has become a vital part of startup decision-making. Companies that have learned all the secrets to leveraging, analyzing, and utilizing credible data can produce more revenue and strive as startupers.

During startup development even the smallest decisions can turn the picture around, so instead of relying on gut feelings, companies now choose to back their decisions up with data. So those who are just entering this topic, let’s take a deep dive into all aspects you might want to know.

The main ways data can power up startup development

Startups are a hard niche to leverage and without the help of data, it can become almost impossible. Data will benefit even the smallest sizes of startups and will play a big role in helping them grow. Here are some examples where data is incorporated for startup growth:

Customers understanding

It’s easy to imagine your ideal customer, their interest, and possibilities, however, there is no guarantee that you will perceive them right. In actual statistics, 70% of the buying experience is based on how a customer is treated.

To treat a customer right you must know exactly their needs and wants and the only way to do so is with data, the kind that will provide insights into their behaviors and preferences.

Pin down new opportunities

When data is organized, analyzed, and turned into various graphs or statistics, there is a great chance to identify new opportunities.

You can discover new markets, interested customers, open segments to enter, and ideas that no one has touched. With all the new discoveries and spreading your startup to different areas, you’ll notice as it starts to grow and develop market-wide.

Data-driven decision making

Startups just like any other similar business are very risky, meaning that the wrong decision, message, or market choice can lead to a costly mistake. These mistakes can be avoided if you use data to make decisions,  write custom messages, or choose the ideal market to invest resources in.

Increase efficiency

Save time, and money, and increase efficiency with startup data. With data collected from your performance metrics or startup success, you’ll be able to identify areas that you can improve, those departments that can be removed, and many adjustments you can make to save your time and costs.

Additionally, data allows the automation of many processes that are either time-consuming, repetitive, or prone to manual mistakes, this will free up your team’s time to focus on more important processes and developments.

Boost your marketing

Developing a startup is important, but how you market it, is what will define its success. Yet again, data will allow you to create the perfect campaign, reach the ideal audience, track the performance of campaigns, and indicate necessary adjustments to make the startup thrive.

Overall studies have even found, that 67% of marketers believe data-driven marketing improves the speed and accuracy of decisions.

Data points you should use for startup success

There are datasets that cover any topics, industries, and customer segments, and defining what data you’ll need is just as important. Every startup industry will have its own set of datasets, but here are three that we can recommend for every startup looking to identify its strongest sales prospects.

  1. Fit Data. These are the basics all startups will need, it includes what company, location, industry, job title, etc., that you are targeting.
  2. Opportunity Data. Data that will help you prioritize the best processes for the right time, whether that includes creating a new campaign or developing communication with prospects.
  3. Intent Data. After defining your fit and opportunity data, intent data will help you isolate prospects that show the most interest in your company, so that you can spend more time catering to them.

Best practices for implementing a data-driven approach in your startups

After the previous information provided, a data-driven approach might seem rewarding but also a complex and overwhelming process. Here are some of the best practices to implement a data-driven strategy in a startup.

Define objectives

Before opting for any data, it’s important that you define your objectives. It’s almost impossible to cover all aspects of a startup, so think of where you want to get started and start by collecting only that type of data.

Collect and analyze the right data

Now that you have defined what data you need, analyze exactly what kind will help you achieve your objectives. For example, if you want to market your startup more, choose data that shows what your audience likes, instead of data about what’s popular in the market.

Use the right tools

Whether you choose to collect data yourself or purchase datasets, it’s important that you use the right software and tools for collection or wisely choose data providers. Always negotiate with providers on terms that will benefit you and won’t affect you if the data isn’t what you need.

Studies show that 29% of marketers identify poor data quality as their primary challenge when working with data-driven marketing.

Moreover, it’s important to pick the right Business intelligence tool to help you make data-driven decisions.

Introduce a data-driven culture

A business will never truly transfer to data-driven if all employees and processes don’t transfer, you can’t have one department working on datasets and the other on a gut feeling. To do so you must inform employees, provide training, and resources, and reward data-driven success.

Test multiple approaches and optimize

A data-driven approach is based on every startup’s unique conditions and position in the market. Don’t stick to one data type, strategy, or campaign, test out various ones to determine which works best for you. Even when you find the ideal approach, don’t relax, always analyze the data you gain to optimize even more.

Final thoughts

A data-driven culture is what will take any startup to its next level of success. Startupers who optimize their data collection processes, analysis routines, and data implementation will overcome many challenges, earn a significant competitive advantage, and be better positioned for growth.

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