Buying and Implementing Data Tools Can Be Easier than It Is Today

Learn six steps data product vendors can take to be buyer-friendly and make it easier to buy and implement data tools.

December 5, 2022
Image of Arpit Choudhury
Arpit Choudhury
Founder, astorik
Buying Data Tools Checklist

The rapid evolution of the data tooling landscape has made the evaluation process more complicated, time-consuming, and overwhelming for most people.

Too many products with distinct core offerings have overlapping capabilities; moreover, the availability of multiple technologies to solve a specific problem has made it harder than ever to choose which one’s suitable based on a team’s needs and the resources they have in terms of implementation.

Often an afterthought for most teams, implementing tools in a manner that people are able to use and derive value from is not trivial—it requires a fair bit of planning which should be done before the tools are even purchased.

That said, there’s only so much teams can do and the onus is on the vendors of data products to ease the process of buying and implementing their products.

It’s up to data vendors to make buying and implementation easy

It’s the collective responsibility of data product vendors to make it easy for buyers to understand the problems their product solves or the needs it fulfills, as well as its core features and benefits—it should be incredibly easy for buyers to figure out whether or not a product can solve a specific problem.

6 ways data vendors can help buyers

Here are six concrete steps vendors can take to become more buyer-friendly:

1. Vendors should be open about what their product cannot do

Sure, data vendors need to describe their product’s core capabilities but at the same time, they should specify clearly what their product can’t do that other products in the same category can.

Looking at data quality as a category, a constant increase in the number of data sources and the amount of data collected has led to an explosion of data quality tools with varying but overlapping capabilities. However, it is rather challenging for buyers to get a clear picture of what some of these tools can do or can’t, and which of the features one needs or doesn’t.

It shouldn’t be hard for vendors to clearly specify what their product is good at and what it doesn’t handle very well—an honest comparison with direct competitors will only build trust in the company’s core offering.

2. Vendors should resist the temptation of creating a new category

Category creation is tempting and something marketers love doing, but at the same time, it also complicates the sales process—buyers need more education to understand the nuances, and sales teams have to work harder to explain what’s different about their product.

Choosing one or more established categories is a more buyer-friendly approach and it also makes it easier for folks to get buy-in from their management—often an arduous process—to invest in a tool operating in an established category.

3. Vendors should invest more in technical documentation and implementation guides

Although this is a no-brainer, vendors spend way more time, effort, and resources on content marketing and branding as compared to educational content and documentation.

Established companies have dedicated teams and a budget to invest in robust documentation and need not compromise on their marketing efforts.

However, early-stage companies—ones that currently dominate the modern data landscape—should make educational resources and implementation guides a priority. Doing so sooner rather than later not only benefits the buyer but also improves the sales process by enabling the sales team to share relevant content to answer a buyer’s questions.

4. Vendors should talk more about the problems they solve and less about their solutions

Data vendors do a pretty good job of talking about how they solve certain problems, but they can do a lot more to build awareness around the problems that exist, what types of companies are usually affected by those problems, and how can teams figure out if they are being affected by those problems.

Monte Carlo, a data observability tool, deserves a mention here as its team continues to do a great job at educating the market about the core problem they set out to solve—data reliability or the lack of it.

5. Vendors should enable collaboration between data and non-data teams

While the primary users of data products are data people, non-data people are the beneficiaries of sound data infrastructure, and vendors should offer capabilities within their products for the two camps to collaborate.

While this is easier said than done, enabling such collaboration can go a long way in better, faster implementation of data tools.

6. Vendors should stop competing on vanity metrics and divert the resources to the above efforts

The data space is experiencing a new trend where vendors are spending a fair amount of effort on benchmarking reports that prove how their products outperform the competition. It’s no surprise that the competition responds with their own benchmarks, proving how the previous benchmark was based on inaccurate assumptions.

Buyers don’t benefit from this and are unlikely to fall for such vanity metrics—everybody will be better off if vendors divert their resources to education and enablement efforts.

Data vendors should choose buyer-friendliness

It’s easy to get carried away in the frenzy of a hot market where data infrastructure startups are being pursued by VCs big and small. But at the end of the day, it’s every vendor’s responsibility as well as in their best interest to choose a buyer-friendly path and make buying and implementing tools less of a pain.

If you’re ready to start using a buyer-friendly solution, get started with a free Amplitude account today.

Behavioral Data Event Tracking
About the Author
Arpit is growing databeats (, a B2B media company, whose mission is to beat the gap between data people and non-data people for good.

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