March 20, 2024

Data Analytics: How Much Does It Cost for a Small/Mid-Sized Company?

Reading time about 9 min

Small-mid-sized companies can expect to spend anywhere between $10,000 to $100,000 per year on data analytics costs. The amount you will pay depends on the number of employees and your business needs. However, companies should set aside approximately 2-6% of their total budget for data analytics.

Data analytics is no longer a thing for only large enterprises. Today, small and mid-sized businesses also generate a sizable amount of data. Business owners can gain helpful insight and make more informed decisions with data analytics.

This post provides everything you need to know about data analytics costs for small and mid-sized companies.

Read on to discover how much you’ll spend while optimizing your business.

Data analytics costs should represent 2-6% of your expenses

Most companies dedicate 2-6% of their total expenses to data analytics, including tools, salaries, and services. 

If a company has a revenue of approximately $2M, it would require almost $100K every year in data analytics costs. This estimate takes into consideration the time that would be spent on the data analysis and reports by all the teams. Ordinarily, this seems like a large amount to spend out of the revenue available, but most companies with this range barely have the required data analytics tools. 

Why it’s worth investing in data analytics

Data has grown due to the influence of the Internet of Things (IoT) and connected devices. It has increased in volume while gaining new diversity and richness. For a business to be successful, the available data network has to be optimized.

The growing importance and use of data analytics have led to the development of new tools, such as customer data platforms. These tools successfully convert raw and unprocessed data into insight.

Good data analysis helps companies make better-informed business decisions and optimize their products and services to deliver a better customer experience. 

72% of organizations claim that data analytics has been critical to their innovativeness. The difference in the performance of more recognized corporations and SMEs has been traced back to analytics. Needless to say, data analytics is important for success in a competitive landscape.

The 3 types of data analytics costs

Today’s cost of investing in data analytics depends on three main factors:

  • The human cost
  • The services you use
  • The tools you choose

In order to make data-driven decisions for long-term growth, you’ll need to spend a good amount on data analytics.

However, simply investing in data analytics tools is not the entire solution.

There are many data analytics costs that need to be considered, and all of this depends on your company. The human cost, services, and tools are all part of the cost, as shown in the table below.

An example breakdown of data analytics costs

1. Human cost

You need people when conducting data analysis, as the end goal is to influence the willingness of your customers. It’s essential to look at how you source and enable the necessary talent. 

The human cost means identifying employees or potential employees who can help integrate data-driven activities within the organization.

Those who already have analytical skills in your company can build their skills to reduce the cost of hiring experts. Adopt user-friendly training with tools that can be accessed by those trusted with the duties.

In doing so, small or medium-sized companies can reduce human costs in the long run. Nonetheless, you may still need to get experts to start the process and train your in-house employees.

2. Services

Your company’s data analytics costs need to include services. For example, there are agencies that do data analysis for other companies. Using an agency would be important in determining the cost for your SME.

For instance, you could contract a customer relationship management (CRM) agency to build some automated marketing workflows. In this case, the agency would spend time unifying some customer data sources. It would help develop a certain level of customer knowledge to aid the analysis or some RFM segmentation and then move on to email marketing workflows.

Just as the human cost, workflow-level costs also play a key role in your company’s data analysis budget.

3. Tools

There are some essential reporting tools that SMEs can use to do cost-effective data analytics reporting. 

SMEs should begin with some popular reporting tools like Google Data Studio. The device is based on Google Sheets data and Google Analytics, which are efficient for analyzing company data.

Companies still find simple business intelligence tools helpful and buy Metabase or PowerBI. The next step is to set up a basic data infrastructure for big data with a data warehouse.

There is Google BigQuery and ETL software like Airbyte or Fivetran. These tools have licenses which vary in how much they cost.

Finally, customer data platforms (CDP) are essential for businesses that need to personalize the customer experience and create a unified view of customer data. CDPs centralize, unify, and sync customer data across a company’s tech stack (CRM, BI, etc) in real or near-real time.

This ensures there is no duplicate data and that teams have access to accurate information for conducting further analytics and creating marketing campaigns. Read more about what a CDP is here.

They also provide your team with interactive dashboards and easy data visualization. You can see profiles and use machine learning to apply scores to easily segment all datasets. CDPs offer a friendly user experience so teams don’t need to rely on IT to get valuable insights. 

Starting prices are usually around $3,000/month. The most competitive offers, such as Brevo, start at $500/month depending on your data volume.

The cost of outsourcing data analytics services vs. in-house data analysts

Data analysts, engineers, or scientists cost differently based on the type of service they offer. 

For many companies, an in-house data science team seems like the only option. Having a team of data analysts is ideal for big companies.

For small and mid-sized businesses, having an in-house data analyst isn’t always possible. Most of these companies turn to outsourcing to start their data analytics journey.

Here is a breakdown of how much an in-house data science team costs vs. the price of outsourcing data services:

Data Analytics consulting firms

Using data analytics firms is known to be reliable for a few reasons. 

  • Consultants are known for their experience in various industries. This makes it easier for them to deliver results faster.
  • Consulting firms are less of a commitment than having to hire a full-time employee. 

However, it’s important to note that traditional consulting firms cost about $50-100 per hour. In some cases, the costs of data analytics consultants are even higher since the job could last weeks or months.

So, working with a consulting firm would cost at least $2,000 – $4,000 weekly. Even though this may be the first option for data analytics for your company, it may not be the most cost-effective. It also may not be a long-term solution because you rely on factors outside of your company.

Outsourced data analytics freelancers

Freelancers can serve the same function as consulting firms while costing less. A single freelancer with enough experience can analyze your company’s data. 

In most cases, the cost of a freelancer depends on the scope of the project, which affects the kind of analysis you’ll need to do. Freelancers are used for short-term projects. Working with freelancers is estimated at $1,000 per week. 

It’s important to note that outsourced freelancers can also differ in their quality, so doing some research beforehand is important.

Also, the return on investment (ROI) and value added to the business can’t be determined. 

Though outsourcing freelancers may help lower costs, it’s important to weigh the pros and cons.

In-house data analytics team

With an in-house consultant, there is someone who is always on call and has been a part of the company for a while. This provides an opportunity to have someone who is considered an outsider handling the company’s analytics. The only thing for this to work is to train the employee to understand your business and industry context.

Having an in-house data analytics consultant streamlines the process of handing over tasks, making it more efficient than relying on external consultants.

However, it can be difficult to find the right data analyst if you’re pressed for time. The hiring process can also be long, so you need to be committed in order to find the perfect fit.

Finally, some people worry that they might not need full-time analysts during the offseason. The minimum cost of keeping an in-house specialist is about $60,000. This is less than what other data analysts cost.

Data analytics costs overview for data scientist, data architect, data engineer.

Some might argue that hiring and integrating a new employee saves money. That’s a good option, but it would still cost the company much more.

Wrapping up data analytics costs

Data is critical for scaling your business because it helps you find and understand behavioral patterns among your customers. By analyzing customer behavior, needs, and data gathered while running a company, you uncover valuable insights. These insights foster innovative thinking and data-driven decision-making.

Data analysis can be done by either an outsourcing firm, a freelancer, or an in-house team for a small or medium-sized company. Each of these options has its advantages and disadvantages. Some are more expensive than others, so they cost differently based on the budget set aside for data analytics costs.

The target for companies is to set aside approximately 2-6% of total budget for data analytics. 

Lower your data analytics costs

Saas data operation tools such as Brevo CDP (customer data platform) can significantly lower the overall cost of data analysis. 

Brevo CDP allows you to centralize your data sources into a single customer profile. From there, you can automatically create and map customer segments into your CRM and analytics tools for faster, streamlined analysis. 

With Brevo CDP, you can say goodbye to data scattered across excel spreadsheets and PDFs and say hello to easy data management.

Lower data analytics costs with Brevo

Centralize and clean your data across your tech stack and connect to your analytics tools for accurate reporting. See how Brevo CDP can help your company save costs.

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