Houston expert breaks down how B2B companies should leverage data for growth

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How you can use your data to improve your marketing efforts. Photo via Getty Images

When focusing on revenue growth in business to business companies, analyzing data to develop and optimize strategies is one of the biggest factors in sales and marketing success. However, the process of evaluating B2B data differs significantly from that of B2C, or business to consumer. B2C analysis is often straightforward, focusing on consumer behavior and e-commerce transactions.

Unlike B2C, where customers can make a quick purchase decision with a simple click, the B2B customer journey involves multiple touchpoints and extensive research. B2B buyers will most likely discover a company through an ad or a referral, then navigate through websites, interact with salespeople, and explore different resources before finally making a purchasing decision, often with a committee giving input.

Because a B2B customer journey through the sales pipeline is more indirect, these businesses need to take a more nuanced approach to acquiring and making sense of data.

The expectations of B2B vs. B2C

It can be tempting to use the same methods of analysis between B2C and B2B data. However, B2B decision-making requires more consideration. Decisions involving enterprise software or other significant business products or services investments are very different from a typical consumer purchase.

B2C marketing emphasizes metrics like conversion rates, click-through rates, and immediate sales. In contrast, B2B marketing success also includes metrics like lead quality, customer lifetime value, and ROI. Understanding the differences helps prevent unrealistic expectations and misinterpretations of data.

Data differences with B2B

While B2C data analysis often revolves around website analytics and foot traffic in brick and mortar stores, B2B data analysis involves multiple sources. Referrals play a vital role in B2B, as buyers often seek recommendations from industry peers or companies similar to theirs.

Data segmentation in B2B focuses more on job title and job function rather than demographic data. Targeting different audiences within the same company based on their roles — and highlighting specific aspects of products or services that resonate with those different decision-makers — can significantly impact a purchase decision.

The B2B sales cycle is longer because purchases typically involve the input of a salesperson to help buyers with education and comparison. This allows for teams to implement account-based marketing and provides for more engagement which increases the chances of moving prospects down the sales funnel.

Enhancing data capture in B2B analysis

Many middle-market companies rely heavily on individual knowledge and experience rather than formal data management systems. As the sales and marketing landscape has evolved to be more digital, so must business. Sales professionals can leave and a company must retain the knowledge of the buyers and potential buyers. CRM systems not only collect data, they also provide the history of customer relationships.

Businesses need to capture data at all the various touchpoints, including lead generation, prospect qualification, customer interactions, and order fulfillment. Regular analysis will help with accuracy. The key is to derive actionable insights from the data.

B2B data integration challenges

Integrating various data sources in B2B data analysis used to be much more difficult. With the advent of business intelligence software such as Tableau and Power BI, data analysis is much more accessible with a less significant investment. Businesses do need access to resources to effectively use the tools.

CRM and ERP systems store a wealth of data, including contact details, interactions, and purchase history. Marketing automation platforms capture additional information from website forms, social media, and email campaigns. Because of these multiple sources, connecting data points and cleansing the data is a necessary step in the process.

When analyzing B2B data for account based marketing (ABM) purposes, there are some unique considerations to keep in mind. Industries like healthcare and financial services, for instance, have specific regulations that dictate how a business can use customer data.

Leveraging B2B data analysis for growth

B2B data analysis is the foundation for any sales and marketing strategy. Collecting and using data from multiple sources allows revenue teams to uncover gaps, trends, and opportunities for continued growth.

Acknowledging what’s different about B2B data and tracking all of the customer journey touchpoints is important as a business identifies a target market, develops an ideal customer profile, and monitors their competitors. Insights from data also single out gaps in the sales pipeline, use predictive analytics for demand forecasting, and optimize pricing strategies.

This comprehensive approach gives B2B companies the tools they need to make informed decisions, accelerate their sales and marketing efforts, and achieve long-term growth in a competitive market.

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Libby Covington is a Partner with Craig Group, a technology-enabled sales and marketing advisory firm specializing in revenue growth for middle-market, private-equity-backed portfolio companies.

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Every situation is unique and deserves a one-of-the-kind data management plan, not a one-size-fits-all solution. Graphic by Miguel Tovar/University of Houston

Houston research: Why you need a data management plan

Houston voices

Why do you need a data management plan? It mitigates error, increases research integrity and allows your research to be replicated – despite the “replication crisis” that the research enterprise has been wrestling with for some time.

Error

There are many horror stories of researchers losing their data. You can just plain lose your laptop or an external hard drive. Sometimes they are confiscated if you are traveling to another country — and you may not get them back. Some errors are more nuanced. For instance, a COVID-19 repository of contact-traced individuals was missing 16,000 results because Excel can’t exceed 1 million lines per spreadsheet.

Do you think a hard drive is the best repository? Keep in mind that 20 percent of hard drives fail within the first four years. Some researchers merely email their data back and forth and feel like it is “secure” in their inbox.

The human and machine error margins are wide. Continually backing up your results, while good practice, can’t ensure that you won’t lose invaluable research material.

Repositories

According to Reid Boehm, Ph.D., Research Data Management Librarian at the University of Houston Libraries, your best bet is to utilize research data repositories. “The systems and the administrators are focused on file integrity and preservation actions to mitigate loss and they often employ specific metadata fields and documentation with the content,” Boehm says of the repositories. “They usually provide a digital object identifier or other unique ID for a persistent record and access point to these data. It’s just so much less time and worry.”

Integrity

Losing data or being hacked can challenge data integrity. Data breaches do not only compromise research integrity, they can also be extremely expensive! According to Security Intelligence, the global average cost of a data breach in a 2019 study was $3.92 million. That is a 1.5 percent increase from the previous year’s study.

Sample size — how large or small a study was — is another example of how data integrity can affect a study. Retraction Watch removes approximately 1,500 articles annually from prestigious journals for “sloppy science.” One of the main reasons the papers end up being retracted is that the sample size was too small to be a representative group.

Replication

Another metric for measuring data integrity is whether or not the experiment can be replicated. The ability to recreate an experiment is paramount to the scientific enterprise. In a Nature article entitled, 1,500 scientists lift the lid on reproducibility, “73 percent said that they think that at least half of the papers can be trusted, with physicists and chemists generally showing the most confidence.”

However, according to Kelsey Piper at Vox, “an attempt to replicate studies from top journals Nature and Science found that 13 of the 21 results looked at could be reproduced.”

That's so meta

The archivist Jason Scott said, “Metadata is a love note to the future.” Learning how to keep data about data is a critical part of reproducing an experiment.

“While this will be always be determined by a combination of project specifics and disciplinary considerations, descriptive metadata should include as much information about the process as possible,” said Boehm. Details of workflows, any standard operating procedures and parameters of measurement, clear definitions of variables, code and software specifications and versions, and many other signifiers ensure the data will be of use to colleagues in the future.

In other words, making data accessible, useable and reproducible is of the utmost importance. You make reproducing experiments that much easier if you are doing a good job of capturing metadata in a consistent way.

The Big Idea

A data management plan includes storage, curation, archiving and dissemination of research data. Your university’s digital librarian is an invaluable resource. They can answer other tricky questions as well: such as, who does data belong to? And, when a post-doctoral student in your lab leaves the institution, can s/he take their data with them? Every situation is unique and deserves a one-of-the-kind data management plan, not a one-size-fits-all solution.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

Here's your university research data management checklist. Graphic by Miguel Tovar/University of Houston

Tips for optimizing data management in research, from a UH expert

Houston voices

A data management plan is invaluable to researchers and to their universities. "You should plan at the outset for managing output long-term," said Reid Boehm, research data management librarian at University of Houston Libraries.

At the University of Houston, research data generated while individuals are pursuing research studies as faculty, staff or students of the University of Houston are to be retained by the institution for a period of three years after submission of the final report. That means there is a lot of data to be managed. But researchers are in luck – there are many resources to help navigate these issues.

Take inventory

Is your data…

  • Active (constantly changing) or Inactive (static)
  • Open (public) or Proprietary (for monetary gain)
  • Non-identifiable (no human subjects) or Sensitive (containing personal information)
  • Preservable (to save long term) or To discard in 3 years (not for keeping)
  • Shareable (ready for reuse) or Private (not able to be shared)

The more you understand the kind of data you are generating the easier this step, and the next steps, will be.

Check first

When you are ready to write your plan, the first thing to determine is if your funders or the university have data management plan policy and guidelines. For instance, University of Houston does.

It is also important to distinguish between types of planning documents. For example:

A Data Management Plan (DMP) is a comprehensive, formal document that describes how you will handle your data during the course of your research and at the conclusion of your study or project.

While in some instances, funders or institutions may require a more targeted plan such as a Data Sharing Plan (DSP) that describes how you plan to disseminate your data at the conclusion of a research project.

Consistent questions that DMPs ask include:

  • What is generated?
  • How is it securely handled? and
  • How is it maintained and accessed long-term?

However it's worded, data is critical to every scientific study.

Pre-proposal

Pre-proposal planning resources and support at UH Libraries include a consultation with Boehm. "Each situation is unique and in my role I function as an advocate for researchers to talk through the contextual details, in connection with funder and institutional requirements," stated Boehm. "There are a lot of aspects of data management and dissemination that can be made less complex and more functional long term with a bit of focused planning at the beginning."

When you get started writing, visit the Data Management Plan Tool. This platform helps by providing agency-specific templates and guidance, working with your institutional login and allowing you to submit plans for feedback.

Post-project

Post-project resources and support involve the archiving, curation and the sharing of information. The UH Data Repository archives, preserves and helps to disseminate your data. The repository, the data portion of the institutional repository Cougar ROAR, is open access, free to all UH researchers, provides data sets with a digital object identifier and allows up to 10 GB per project. Most most Federal funding agencies already require this type of documentation (NSF, NASA, USGS and EPA. The NIH will require DMPs by 2023.

Start out strong

Remember, although documentation is due at the beginning of a project/grant proposal, sustained adherence to the plan and related policies is a necessity. We may be distanced socially, but our need to come together around research integrity remains constant. Starting early, getting connected to resources, and sharing as you can through avenues like the data repository are ways to strengthen ourselves and our work.

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This article originally appeared on the University of Houston's The Big Idea. Sarah Hill, the author of this piece, is the communications manager for the UH Division of Research.

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Houston battery tech startup FlowCellutions acquired by Katy energy co.

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Katy-based TerraFlow Energy, an energy storage and infrastructure company, has acquired Houston-based battery technology startup FlowCellutions. Financial terms weren’t disclosed.

FlowCellutions still operates under its established name, but with the tagline “A TerraFlow Energy Company.” Becca Segel, founder and CEO of FlowCellutions, now runs the business as its president.

FlowCellutions specializes in electrochemical sensing, diagnostics, analytics, and testing that offer insights into battery chemistry, charging capabilities, and system performance.

“FlowCellutions has always been focused on developing better ways to understand what is happening inside a flow battery and using that information to improve how these systems perform,” Segal said in a press release. “Joining TerraFlow gives us the opportunity to apply that work at a much larger scale while continuing to build the capabilities and expertise that make FlowCellutions unique.”

The FlowCellutions platform supports data centers and other heavy users of power. It’s designed to help reduce operating costs, prevent failures and costly downtime, and extend battery lifetime from about seven years to more than 30 years.

Segel founded the company in 2022. A member of Greentown Labs, the company raised more than $2 million in non-dilutive funding and received $1.5 million in National Science Foundation funding earlier this year.

FlowCellutions is one of five finalists in the Energy Transition Business category of InnovationMap’s 2026 Houston Innovation Awards.

“FlowCellutions brings a depth of scientific and technical expertise that fits naturally with where TerraFlow is going,” Jon Parrella, CEO of TerraFlow, said in the release.

“As we move from developing these systems to deploying them at commercial scale, understanding performance at a deeper level matters,” he said. “Bringing FlowCellutions into TerraFlow strengthens that capability and gives both teams more opportunity to advance the technology.”TerraFlow, founded in 2024, develops long-duration energy storage and power infrastructure for data centers, industrial facilities, utilities and other large power consumers.

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This article originally appeared on EnergyCapitalHTX.com.

3 fast-growing Houston scaleups named Innovation Awards finalists

meet the finalists

From IPOs to groundbreakings, some of Houston's most innovative companies reached major milestones this year.

As part of the 2026 Houston Innovation Awards, our Scaleup of the Year category honors innovative later-stage startups that have recently reached a significant milestone in company growth. Three scaleups have been named finalists for the 2026 award.

Read more about these businesses, their founders and their breakthrough technologies below. The 2026 winners will be announced on InnovationMap.com in mid-November.

Erock

Energy infrastructure company Erock, previously known as Enchanted Rock, develops dual-purpose microgrids that rely on natural gas and renewable natural gas to produce lower carbon emissions and air pollutants than diesel generators. Its products can provide bridge power before grid interconnection, backup power during outages and dispatchable capacity that supports long-term grid reliability. The company has more than 1,100 megawatts of installed capacity and over 20 years of experience serving commercial, municipal and large-scale technology customers.

Erock completed its initial public offering this year, raising approximately $600 million in gross proceeds. It also grew its contracted power system sales backlog to approximately $1.7 billion, up tenfold year-over-year, with production sold out through 2028, according to the company's application. The company secured a major equipment order from Anthropic, began construction of the 366-megawatt El Paso Electric project supporting Meta's data center campus, and started assembly operations at its Hyperion facility in Cypress, Texas.

Hertha Metals

Hertha Metals produces lower-cost, lower-emission steel and high-purity iron. The company has developed a single-step process that uses natural gas as a direct reductant instead of metallurgical coal, which cuts production costs by more than 25 percent and emissions by up to 50 percent, according to the company. The same process produces high-purity iron needed for high-purity steels and rare earth magnets. The company says it aims to "re-industrialize America’s production of critical materials."

Hertha Metals was founded by CEO Laureen Meroueh in 2022 and emerged from stealth last year with more than $17 million in venture capital funding. The company closed a $133.65 million Series A this month and also broke ground on its $100M high-purity iron factory known as Chalyx in Conroe.

Venus Aerospace

Spacetech company Venus Aerospace is developing a high-thrust rotating detonation rocket engine (RDRE) that replaces the subsonic combustion used in conventional rocket engines. The RDRE is a compact, simpler engine that can deliver up to 15 percent greater efficiency for defense and space applications. It completed its first U.S. flight test of the engine last summer.

Venus Aerospace was founded in 2020 by CEO Cassie Duggleby and CTO Andrew Duggleby. It raised a $20 million Series A in 2022 and $42 million Series A2 in 2025. It closed a $91 million Series B earlier this year and expanded its leadership team. The company is working toward longer-duration and higher-thrust testing and advancing its flight program.

Texas ranks among top 10 best states for jobs in new report

jobs report

Business boosters often describe Texas as an economic engine. A new ranking from personal finance website WalletHub underscores that assessment.

WalletHub put Texas at No. 8 on its new list of the best states for jobs. Nebraska grabbed the No. 1 spot, and West Virginia landed at No. 50.

To compile the list, WalletHub evaluated 34 metrics from two categories: job market and economic environment. It then crunched the numbers to create a score for each state. A score of 100 represents the most favorable conditions for job seekers.

Texas ranked 25th in the job market category and second in the economic environment category. Texas’ eighth-place showing was based on a score of 59.23.

“The best states for jobs make it easier for residents to find and retain jobs, and employers in these states also offer very competitive compensation and benefits,” WalletHub analyst Chip Lupo said. “In addition, the top states are great places for people looking to raise a family, ranking among the best states for working parents.”

Data released in late October shows Texas led all states for job growth during the 12-month period that ended in September. In that time, Texas added 154,300 jobs at an annual rate of 1.1 percent.

“Texas is America’s jobs leader,” Gov. Greg Abbott said in a press release. “Businesses big and small invest with confidence in Texas and in our growing and skilled workforce. That means bigger paychecks for more Texans and more opportunities for Texas families to prosper for years to come.”

Abbott noted Texas reigns as the top state for attracting job-producing businesses and creating jobs at small businesses.

The Houston metro area actually saw a decline in new jobs in September, losing 7,300 jobs compared with the previous month. On a year-over-year basis, the region added 13,500 jobs, with professional and business services, construction, and private education and health services leading the growth.

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