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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UTHealth Houston team joins NASA initiative to protect border drinking water

water watch

Climate change means far more to public health than living with hotter days. Transformations in our weather are contributing to challenges in accessing safe drinking water in some communities.

One of the most dire situations is along the US–Mexico border. The National Aeronautics and Space Administration (NASA) is seeking to address that issue with its Water Quality Applications program. An 11-researcher project led by a UTHealth Houston School of Public Health faculty member has been selected to participate.

“Drinking water is one of the most fundamental public health protections, but producing safe drinking water involves a delicate balance,” Yun Hang, assistant professor of environmental and occupational health sciences, said in a news release. Her team’s proposal was one of 93 that were submitted for funding through NASA’s Research Opportunities in Space and Earth Sciences (ROSES)-2025 program.

This is the first time that NASA has worked with a team devoted to water quality applications. The group, which includes researchers from across the nation, will use satellite observations of Earth, as well as hydrologic modeling, to potentially anticipate and act on water quality conditions as they change. Challenges addressed over the course of the three-year program, which kicked off in June, might include problems with water quality due to climate variability and increased pressure on water resources.

Hang’s team will focus on a pair of borderlands: Paso del Norte and the Rio Grande Valley.

“Working closely with El Paso Water ensures that our research addresses real operational needs while helping utilities better prepare for climate-related water quality changes and continue providing safe drinking water to communities across the Texas border region,” Hang added in the release.

She and the team will use data gathered by NASA on both past and future Earth-observing missions, which will allow them to track environmental changes that may affect source water quality. Combined with past water treatment records and hydrologic models, the team will also utilize artificial intelligence to develop predictive tools that aim to stop issues before they become larger hurdles to water safety.

Another one of the project’s goals is to create visualization tools and source water summaries that can be utilized by those without scientific expertise. The tools will be produced in English and Spanish to further broaden their accessibility.

The hope is that the materials made by the team will also go far beyond the border, with protocols that can be adapted or adopted by other areas dealing with water quality issues.

U.S. News declares Houston hospital No. 1 in Texas for the 15th year

Top of the Chart

Houston Methodist Hospital and over a dozen more Houston-area hospitals have earned bragging rights in U.S. News & World Report's newly released rankings of the Best Hospitals for 2026-2027.

Every year, U.S. News annually evaluates nearly 4,500 U.S. hospitals to determine which meet the publication's rigorous standards and offer the best care for patients across 14 adult specialties and 23 procedures and conditions. New to this year's batch of rankings, U.S. News introduced regional rankings in cancer; cardiology; heart and vascular surgery; orthopedics; and rehabilitation.

Houston Methodist Hospital was the only Texas institution named on U.S. News' Best Hospitals Honor Roll, a prestigious list of the 20 best medical centers in the country. Houston Methodist also reigns as Texas' best hospital for the 15th consecutive year.

The hospital also shines among the nation’s best in 10 specialties:

  • No. 5 – Gastroenterology and GI Surgery
  • No. 7 – Obstetrics and Gynecology
  • No. 10 – Cardiology, Heart, and Vascular Surgery
  • No. 11 – Pulmonology and Lung Surgery
  • No. 13 – Neurology and Neurosurgery
  • No. 19 – Cancer
  • No. 21 – Orthopedics
  • No. 23 – Diabetes and Endocrinology
  • No. 24 – Geriatrics
  • No. 43 – Urology
Houston Methodist also earned high performing distinctions across one regional specialty (Rehabilitation) and 21 procedures and conditions.

"This recognition reflects the remarkable dedication of our physicians and employees and their tireless focus on delivering unparalleled care to our patients," said Houston Methodist president and CEO Marc L. Boom, M.D. in a press release. "While we are honored by this recognition, its true significance lies in what it represents — an unwavering commitment to putting patients first."

Elsewhere in Houston, The University of Texas MD Anderson Cancer Center ranked as the No. 1 best cancer hospital in the nation for the 12th year in a row.

"This ranking is a tremendous honor, and it reflects our unwavering commitment to continue making progress in our mission to end cancer," said UT MD Anderson president Peter WT Pisters, M.D. "We are deeply grateful to everyone who made this recognition possible: our faculty and staff, volunteers, donors, and the patients and families we are honored to serve."

MD Anderson also earned national rankings in two specialties — Urology (No. 6) and Gastroenterology and GI Surgery (No. 16) — and it received high performing distinctions in six procedures and conditions: Colon Cancer Surgery; Ear, Nose, and Throat Surgery; Gynecological Cancer Surgery; Leukemia, Lymphoma, and Myeloma Treatment; Lung Cancer Surgery; and Prostate Cancer Surgery.

The additional Houston hospitals that ranked among the best in Texas for 2026-2027 are:

  • No. 3 – Houston Methodist Sugar Land Hospital (tied with Baylor University Medical Center Dallas)
  • No. 5 – Baylor St. Luke's Medical Center, Houston
  • No. 6 – Memorial Hermann Hospital, Houston
  • No. 7 – Houston Methodist The Woodlands Hospital
  • No. 10 – Memorial Hermann Greater Heights Hospital (tied with St. David's Medical Center, Austin)
  • No. 14 – Houston Methodist Baytown Hospital
  • No. 15 – Memorial Hermann Memorial City Medical Center, Houston
  • No. 21 – Houston Methodist Clear Lake Hospital, Nassau Bay; St. Luke's Health-The Woodlands Hospital; University of Texas Medical Branch, Galveston (also tied with six more Texas hospitals)
  • No. 30 – Memorial Hermann Sugar Land Hospital (tied with five other Texas hospitals)
  • No. 36 – HCA Houston Healthcare Kingwood (tied with Parkland Health-Dallas)
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This article originally appeared on CultureMap.com.

Houston helps power Texas’ rise as AI infrastructure hub, new report finds

eyes on ai

Houston plays a major role in Texas’ rapidly evolving AI economy, a new report indicates.

The report from Build American AI, a pro-AI advocacy group, notes Houston’s growing AI presence includes:

  • A factory being built by AI chipmaker NVIDIA and electronics manufacturer Foxconn that will produce AI supercomputers and infrastructure systems
  • Houston Methodist’s use of ambient AI to listen to health care providers’ conversations with patients, eliminating the need for manual notetaking
  • An abundance of AI products and services for the energy sector

Across the state, billions of dollars in new AI investments are fueling advancements in construction, manufacturing, energy production, logistics, and health care, according to the report.

“Texas is not merely a place where AI products will be used. Texas is becoming one of the places where the AI economy is being assembled,” the report says.

Particularly noteworthy are four major AI-related projects around the state representing an investment of more than $140 billion, including Google’s $40 billion buildout of AI data centers.

“While California had a headstart in building the software era, Texas will build the infrastructure era,” says the report. “That is not a slogan. Economic research has revealed for decades that innovation happens where the local conditions make building and collaboration possible, and Texas is positioned to be a central hub.”

According to the report, components of Texas’ infrastructure era include:

  • Energy leadership
  • Top-tier hospitals
  • Semiconductor investments
  • Construction capabilities
  • Data center growth
  • Major companies and universities

On the workforce front, Stanford University’s 2026 AI Index found Texas had 80,547 AI job postings in 2025, accounting for 8 percent of the national total.

“Texas no longer needs to ask whether AI will reshape the economy. It already has,” the report concludes. “The question is whether Texas will merely host part of that future or lead it.”

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