Choosing BI and data visualization tools can seem like an overwhelming task – there are many options, each of which is consistently making enhancements and improvements. Meanwhile, your business is not going to stop while you evaluate and implement a data visualization tool.

It’s easy to want to choose the one that makes the prettiest graphs, or the least expensive, or the one you’ve used in the past. Thinking comprehensively about how this tool will be used and fits within your business is important to make sure you’re making the most educated long-term decision.

Tableau, Looker, Power BI, Domo and Sigma are among the most common choices for DTC and B2C businesses. As you evaluate these different data visualization tools, we’ve categorized the decision process into three key components to use as a guide as you choose the best BI software for your business.

END USER NEEDS

It’s often said in consumer businesses that one should start with the customer experience and work backwards. This framework also works well when thinking about data visualization tools – what do your clients need now and in the future?

Who will use the BI / data visualization tools now and how will they use it?

1. Leadership receiving clean, consistent, high-level reporting with limited interaction – for example, Tableau is great at polished reports delivered via PDF or in browser
2. Operators engaging with pre-built dashboards to make data-driven decisions – Tableau, Power BI, and Looker all excel at allowing end-users to have controlled interaction with dashboards
3. Financial analysts digging into data for ad hoc analysis and delivering insights to functional teams – Power BI is great if analysts are already Excel gurus
4. Finance and planning teams exporting data for use in offline models – while it would be great for all modeling to be done within the BI stack, often that isn’t feasible (at least not right away). Domo and Sigma are somewhat more ‘export-friendly’ than some other tools
5. Field teams receiving detailed performance updates on their mobile device to prioritize their daily activities – most tools have mobile apps to consider if this is a heavy use-case

What do your team’s future needs look like?

1. Choosing a BI or data visualization tool that meets today’s needs is paramount, but planning for the future is also critical. Are you planning to ramp up teams of analysts or data scientists? Sales and operations teams? Creating external-facing reports?
2. Defining how your company’s growth plans will impact who uses your data visualization tool and how they’ll engage with it is instructive in choosing a tool that will stand the test of time.

What level of permission-setting will you need? Will all data be available to all users or will you want highly customized permission groups?

DATA PLATFORM

Most BI and data visualization tools can be used across a variety of tech set-ups, but some do fit more seamlessly. For example, if your organization works fully with the Google stack and your team are Google Cloud experts, Looker may be a good option. If you’re building a flexible more modular data platform you have many options such as Tableau, Looker, or Sigma.

What does your data stack look like currently and in the future?

1. Modular: might use different vendors for data acquisition, data transformation, data warehousing, and data visualization tools
2. Vendor-specific: many visualization tools are part of large enterprises that offer complete data platforms (e.g., Power BI is part of Microsoft’s suite, Looker is part of Google’s)
3. TBD: often, our clients are in the process of figuring this out and don’t have a comprehensive plan yet – we can help formulate that plan

IMPLEMENTATION AND SWITCHING COSTS

A key component of choosing the right data visualization tool is of course, costs and implementation. From set-up fees and ongoing licensing cost to planning how the implementation will be handled there is a lot of considerations. Will your internal team reprioritize efforts and focus on BI tool selection and implementation? Will you rely solely on consultants? Do you want to explore a hybrid approach, where consultants (like us!) supplement your team through this process?

Key questions to explore include:

1. What critical reporting needs to be immediately available?
2. What changes to the data platform need to be made and how are they sequenced?
3. How will the new tool be communicated and rolled out across the organization?
4. What are the hard costs? Licensing fees and consultant costs?
5. What about future transitions? It would be great to choose a solution that will last forever, but with the continuous changes in the BI marketplace as well as within your company that is just not realistic. It is worth spending some time thinking through what future changes to your technology stack, data warehouse, or business model would mean for your BI tool. If your full data stack is modular, future transitions will look different than if a comprehensive vendor solution is in your future.

Selecting and rolling out a new BI / data visualization tool can be both challenging and exciting. Spending some time up front documenting your needs and evaluating options through that lens will lead to a successful choice. There are many tools to choose from and considerations to think through.