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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5 female-founded Houston startups shine as Innovation Awards finalists

meet the finalists

Houston is home to many standout female founders, making inroads and breakthroughs in every industry.

As part of the 2026 Houston Innovation Awards, our Female-founded Business category honors women-led startups that are shaping Houston innovation.

Five female-founded businesses have been named finalists for the 2026 award. This year's finalists, selected by our esteemed panel of judges, range from an AI startup for C-Suite execs to a company developing semi-autonomous crawler robots for corrosion detection.

Read more about these innovative startups and the visionary female founders behind them below. The 2026 winners will be announced on InnovationMap.com in mid-November.

Adair

Artificial intelligence startup Adair uses computational linguistics and behavioral economics to measure, model and quantify the impact of spoken and written language on firm valuation and stock prices. The company works with C-Suite executives of public companies on high-stakes communications before they go live.

The company was founded last year by CEO Kathleen Perley, CPO Alex Duong and CTO Anthony Grivet. It raised $5.6 million earlier this year, according to its application.

ARIX Technologies

Energytech startup ARIX Technologies has developed a semiautonomous VENUS crawler robot to detect corrosion under insulation before it becomes a failure. The robots climb insulated piping in refineries, chemical plants and energy facilities to capture inspection data without removing insulation or building scaffolding. ARIX's inspection portal then turns information from the inspection into data a company can act on.

ARIX was founded in 2017 by Dianna Liu, who serves as director, and Head of Product Petter Wehlin. Craig Malloy serves as CEO. The company has raised more than $22 million in seed funding and a Series A round, according to its application.

Bairitone Health

Healthtech startup Bairitone Health is bringing anatomy imaging for sleep apnea to the home environment. The company's platform maps users' anatomy during natural sleep using a facial patch to determine the root cause of airway obstruction. It then offers effective therapies for each patient.

The company was founded in 2022 in the Texas Medical Center's Biodesign program by CEO Meagan Pitcher, CTO Onur Kilic and chief medical officer Britt Cross. It was a member of Activate Houston's inaugural cohort and has participated in numerous accelerators and incubators. The company raised an oversubscribed seed round for $2.4 million earlier this year and received Breakthrough Device Designation from the Food and Drug Administration in April.

FlowCellutions

Energytech startup FlowCellutions is developing a chemistry-agnostic diagnostics platform for flow and metal-air batteries supporting data centers and critical infrastructure. The platform is designed to help reduce operating costs, prevent failures and costly downtime, and extend battery lifetime from approximately seven years to more than 30 years. It has deployed four paid pilots and plans to take insights from the programs to develop its next-gen sensor platform technology.

CEO Becca Segel founded the company in 2022. It is a member of Greentown Labs, and Segel was a 2025 Activate Fellow. The company has raised over $2 million in non-dilutive funding and received a $1.5 million NSF SBIR Fast-Track award earlier this year.

ParaDocs Health

Healthtech startup ParaDocs Health is developing a clinical intelligence platform that helps doctors and care teams streamline administrative tasks and make better use of patient records. Its technology organizes fragmented clinical data into actionable insights, helping care teams identify gaps in care, assess patient risks and simplify documentation and reimbursement.

ParaDocs was founded in 2022 by CEO Dr. Dhini Nasution and CTO Dr. Omar Mohtar. The company participated in the TMCi Biodesign Program and raised a preseed round last year, according to its application.

Rice University launches AI initiative, plans to hire 75 faculty

ai expansion

Houston’s Rice University announced a university-wide artificial intelligence initiative this week that includes hiring 75 new AI-focused faculty. It also shared new details about its planned state-of-the-art facility, The Arc.

Fresh off the announcement of Rice’s new Master of Artificial Intelligence (MAI) coming next fall, the university shared that it plans to expand its AI-related courses and be a “global leader in advanced computing and responsible AI.”

Rice reports that it has already hired 35 faculty members to deepen expertise across schools and departments regarding AI, and plans to recruit 40 more across disciplines including engineering, computing, health, energy, environmental resilience, business, humanities and the arts.

Rice's schools and departments have identified the four cluster areas to guide its hiring:

  • Foundational AI
  • AI for Health
  • AI for Energy, the Environment and Resiliency
  • Responsible AI: Society and Ethics

“Hiring exceptional faculty is essential, but it is only one part of the equation,” Amy Dittmar, Rice’s Howard R. Hughes Provost and executive vice president for academic affairs, said in a news release. “We are building the people, places and partnerships needed to advance AI from foundational discovery to societal impact.”

Another major component of the effort is the planned 200,000-square-foot facility, The Arc, which Rice announced will break ground this fall. Rice will occupy nearly 80,000 square feet of office and laboratory space dedicated to topics including AI, data science, robotics, computational engineering and energy. The university previously announced that The Arc would be completed in Q1 2028.

The Arc will also house the AI Foundry, which is being developed as a collaborative space for industry partners, scientists and students.

“As Rice grows, we are being intentional about where we invest and how we build,” Rice President Reginald DesRoches added in the release. “By bringing together exceptional faculty, a strong interdisciplinary research community, world-class facilities and Houston’s extraordinary innovation ecosystem, Rice has an opportunity not simply to participate in the AI revolution but to help define its future.”

5 minority-founded startups shaping the future of Houston innovation

meet the finalists

Houston’s startup ecosystem reflects the diversity of the city itself.

As part of the 2026 Houston Innovation Awards, our Minority-founded Businesses category will honor an innovative Houston startup founded or co-founded by BIPOC or LGBTQ+ representation.

Five minority-founded businesses have been named finalists for the 2026 award. The finalists, selected by our esteemed panel of judges, range from an AI edtech startup to a company operating in the floating offshore energy infrastructure sector.

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

AI Made Fun

Edtech startup AI Made Fun is working to close the gap in AI education by teaching K-12 students how to understand and responsibly use artificial intelligence. The company has developed a comprehensive AI literacy curriculum with 60 modules, animated videos, interactive activities, teacher guides and family resources. Its curriculum covers how AI works, misinformation, algorithmic bias, data privacy, online safety and academic integrity.

AI Made Fun was founded in 2025 by Devshree Golecha. It launched in classrooms this school year with five licensed schools serving more than 800 students. The company is pursuing partnerships with Houston-area school districts, including Houston ISD and Alief ISD, and has pledged free and subsidized access for underserved communities.

Deep Anchor Solutions

Offshore energy consulting and design company Deep Anchor Solutions wants to help scale floating offshore energy infrastructure by removing anchoring as a barrier. Its deeply embedded ring anchor (DERA) technology can be installed quietly without heavy-lift vessels, reducing anchor-related costs by up to 75 percent and lifecycle CO2 emissions by up to 80 percent.

The company was founded in 2023 by CEO Junho Lee and technical advisor Charles Aubeny. Lee earned his Ph.D. in geotechnical engineering from Texas A&M University, where Aubeny is a professor of civil and environmental engineering. The company has participated in numerous accelerators and incubators, including Greentown Labs, MassChallenge, EnergyTechNexus LiftOff and others. Lee was an Activate 2025 fellow.

HEXAspec

Rice University spinout HEXASpec is working to improve the sustainability and thermal conductivity of semiconductor chips. The company has developed breakthrough inorganic fillers that allow graphic processing units (GPUs) to use less water and electricity and generate less heat.

HEXASpec was founded in 2025 by CEO Tianshu Zhai, CTO Jing Zhang and chief product officer Chen-Yang Lin. It has raised $800,000 in pre-seed funding and another $1.5 million in non-dilutive grants, according to the company's application. The startup won the Liu Idea Lab for Innovation and Entrepreneurship's H. Albert Napier Rice Launch Challenge in 2024 and the 2025 Energy Venture Day and Pitch Competition during CERAWeek in the TEX-E student track in 2025. It was awarded a $500,000 National Science Foundation Partnership for Innovation grant last summer.

Prana Surgical

Health tech company Prana Surgical is developing a minimally invasive surgical platform for small, hard-to-reach lung nodules that may be cancerous. The company's Prana System cleared U.S. Food and Drug Administration (FDA) approval earlier this year.

Prana Surgical was originally founded as Prana Thoracic in 2022. It has participated in numerous accelerators, including the Texas Medical Center Innovation Accelerator in 2023 and the IGNITE Health accelerator in 2022. It raised $6 million in Series A funding rounds in 2023 and 2024 , with a Series B currently ongoing. The company said in its application that it is currently moving into the next stage of clinical validation and revenue generation in the U.S., in addition to preparing its manufacturing and commercial infrastructure for broader use.

Torres Orbital Mining Inc.

Space tech company Torres Orbital Mining is developing autonomous excavation and material preprocessing systems to move and process granular materials while reducing workers’ exposure to hazardous dust. The company is initially commercializing its technology for Earth-bound applications—including silica sand, recycled glass and mine tailings—though the technology is also designed to support future lunar mining operations. The company aims to accelerate a permanent and ethical human presence on the Moon.

CEO Luis Torres founded Torres Orbital Mining in 2025. The company is a member of Greentown Labs and has participated in accelerators like the ESRIC Space Resources Startup Program and Capital Factory All Access Fund. The company received a six-month, $225,000 SBIR Phase I contract from NASA in August.

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