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

guest column

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.

------

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.

From Your Site Articles
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.

------

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.

------

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.

Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

Property Showcase

New probe into Tesla after vehicle slams into Houston-area home at high speed

Tesla Talk

The top U.S. auto regulator opened an investigation Monday, June 22, after a Tesla using an automated driving feature slammed into a Texas home at high speed and killed a 76-year-old woman standing inside.

The National Highway Traffic Safety Administration said it's opening a special investigation into the Tesla Model 3 crash on Friday near Houston, a significant probe because the car was using technology that Elon Musk considers key to the company's future.

The Tesla CEO is rolling out robotaxis using automated software in several U.S. cities this year and plans to invite Tesla owners to put their cars into the fleet using the same system across the country.

The driver told the Harris County Sheriff's Office that he was using the technology, according to a police report on the crash, but it's not clear what role, if any, it played in the incident.

Tesla did not respond to a request for comment but the head of the company's artificial intelligence efforts suggested on social media later Monday that the self-driving feature was not to blame.

“In this case, the driver manually overrode self-driving by pressing the accelerator all the way to 100% of the accel pedal in this residential area,” wrote Ashok Elluswamy on X, the platform that is now part of Musk's rocket company, SpaceX. “They reached a speed of 73 mph during the crash, and had the accelerator pressed even after the crash.”

The police report noted that the driver was not drunk and is cooperating. It identified the woman killed as Martha Avila.

Video obtained by KHOU-TV shows the car traveling at top speed over the front lawn of a brick home in Katy, then ramming into a front room. The next shot shows the car encased in the home amid piles of crumbling plaster, split beams and bits of furniture.

The auto safety regulator, known as NHTSA, has launched several investigations into Tesla, including one late last year into 58 incidents in which Teslas reportedly violated traffic safety laws while using self-driving technology, leading to more than a dozen crashes and fires and nearly two dozen injuries.

A few months earlier, the NHTSA opened an investigation into why Tesla apparently had not been reporting crashes promptly as required.

As for special crash investigations, the NHTSA has opened 46 involving Teslas using self-driving or driver-assistance technology over the past decade, according to the agency's records. In more than a dozen of those crashes, at least one person — a driver, passenger or pedestrian — was killed.

Tesla stock fell sharply early last year as car sales plunged amid a boycott of Musk after he waded into politics, leading President Donald Trump's budget-cutting Department of Government Efficiency initiative and embracing European extremist candidates.

Musk has since shifted the Tesla story to one less about car sales and more about AI and robotaxis, and done so successfully. The stock is up 16% in the past year.

Intuitive Machines lands $1M grant to expand robotics operations

Expansion mode

Houston-based Intuitive Machines is expanding its operations around the country.

The space tech company—which has offices and labs in Texas, California, Arizona, Colorado and Maryland—announced that it has received a $1 million grant from Maryland Gov. Wes Moore through the state's Build Our Future Grant. The funding will go toward expanding Intuitive Machines’ Super Cislunar Robotics Assembly Building (Supa-CRAB) Mechanisms and Robotics Center of Excellence in Anne Arundel County.

The company will move into a 69,000-square-foot facility and build out additional lab and office space. It will also procure equipment that will allow for in-house Assembly, Integration and Test (AI&T) activities, according to a news release. Intuitive Machines says the expansion will take place this fall.

“This collaboration shows how industry, state programs, and education can reinforce one another,” Steve Altemus, CEO of Intuitive Machines, said in the release. “Maryland invests in innovation, companies grow and hire, students gain experience, and communities benefit from new opportunities and long-term career pathways. Together with Governor Moore, the state of Maryland, and Anne Arundel County leaders, we are building a permanent path to long-term lunar operations, an advanced robotics and mechanisms center of excellence, and a technology edge for our nation.”

Intuitive Machines first launched operations in Maryland in 2021 and has since expanded five times in the state. The company officially opened its robotics and mechanisms facility in 2024.

The Maryland team has built robotics and mechanisms for the Nova-C landers and IM-1 and IM-2 missions. In the future, Intuitive Machines expects the Maryland team to work on its IM-3 Rover Deployment Mechanism (RDM), a 360 pan-tilt camera for panoramic views, the Main Engine Gimbal (MEG), and the company's first data relay satellite, known as Altus-1.

Intuitive Machines moved into a new $40 million headquarters at the Houston Spaceport in 2023. The company announced an expansion of its lease last year.

The company announced a $175 million equity investment to fuel growth in March. It's since landed a $180 million NASA CLPS award to deliver seven payloads to the moon's Mons Malapert on the IM-5 mission.

5 Houston universities named best in the world on new U.S. News list

Top of the Class

Five Houston-area universities have been named among the best universities worldwide in U.S. News & World Report's just-released comprehensive list for 2026-2027.

U.S. News' Best Global Universities report ranks more than 2,250 schools based exclusively on their academic research performance and international reputation. Only 275 universities from the U.S. were included in the global ranking, and 21 based in Texas.

Harvard University topped the list for 2026-2027, and the Massachusetts Institute of Technology and Stanford University claimed the coveted No. 2 and No. 3 spots worldwide.

Houston's Baylor College of Medicine topped the list of the best local schools, and it ranked as the 144th best university in the world.

Here's how the rest of Houston's local institutions ranked:

  • No. 201 – Rice University
  • No. 324 – University of Texas Health Science Center Houston
  • No. 390 – University of Houston
  • No. 599 – University of Texas Medical Branch Galveston

In a statement explaining global university trends, the managing editor for Education at U.S. News, LaMont Jones, Ed.D., said schools in the U.S. have continued to rank "disproportionately high" while major universities from other countries in China and South America are starting to catch up.

"The continuing strength of [American university] reputations and academic research are, for the most part, unmatched," he said. "It's why students all over the world flock here to learn."

Top-ranking Texas universities
The University of Texas at Austin ranked No. 1 statewide and No. 56 worldwide, further cementing the university's reputation as the top choice for students seeking a higher education in Texas.

Earlier in June, UT Austin ranked No. 35 in a separate list of the best universities in the world from the Center for World University Rankings, which compared 2,000 schools globally.

Here's where other Texas universities stand among the top 1,000 in this year's global rankings:

  • No. 113 – University of Texas Southwestern Medical Center, Dallas
  • No. 177 – Texas A&M University, College Station
  • No. 296 – University of Texas at San Antonio
  • No. 451 – Baylor University, Waco
  • No. 503 – University of Texas at Dallas
  • No. 562 – Texas Tech University, Lubbock
  • No. 739 – University of North Texas, Denton
  • No. 975 – University of Texas at Arlington
  • No. 944 – Southern Methodist University, Dallas
Additionally, six Texas universities ranked outside the top 1,000: University of Texas Rio Grande Valley (No. 1,153); University of Texas El Paso (No. 1,238); Texas State University in San Marcos (No. 1,531); Texas Tech University Health Sciences Center in Lubbock (No. 1,871); Texas Christian University in Fort Worth (No. 1,906); and Sam Houston State University in Huntsville (No. 2,141).

---

This article originally appeared on CultureMap.com.

View All Listings