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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Planned KBR spinoff scores $1B NOAA deal for extreme weather forecasting

weather watch

Amid a major spinoff, Houston-based KBR's Mission Technology Solutions business has been awarded a five-year contract for up to $1.1 billion from NOAA’s National Weather Service to help predict and combat extreme weather conditions.

Under the follow-on Commercial Data Program National Mesonet Program (CDP NMP) contract, KBR will provide weather and observational data from commercial stations, university and research campuses, and other non-federal providers nationwide. The information collected will assist in predicting severe temperatures and high-impact weather conditions like extreme storms.

"This award underscores KBR's proven track record of delivering vital data that strengthens national forecasting capabilities," Todd May, KBR’s senior vice president of Mission Technology Solutions, said in a news release.

According to a separate release from NOAA, the contract expands upon KBR's existing relationship with the agency. KBR will work with about 70 private industry partners on services such as data recording, collection, aggregation and processing, and will lead the CDP NMP's "network of networks."

“NOAA gathers environmental information from a wide variety of sources, and a growing list of private industry partners have joined our agency to collect this vital data,” Ken Graham, director of NOAA’s National Weather Service, said in the release. “This agreement streamlines the process that turns raw data into the gold-standard forecasts that Americans depend on.”

KBR will utilize its Speed to Mission ImpactSM technology for the project to supply data from across regions, measurement types, and system configurations. Both KBR and NOAA say the expanded data collection contract will help the agency create more accurate and timely forecasts, particularly for severe weather and extreme events, while also creating a path for new weather-observation technologies.

KBR has supported the CDP NMP for more than 9 years. The program will be managed in Greenbelt, Maryland.

"We're driving expanded integration of commercial sensor and data sources into this platform and are honored to know our work helps forecasters give their communities earlier warnings and more time to prepare for dangerous weather,” May added in a release.

KBR’s Mission Technology Solutions business will be rebranded as Trinzic after its planned spin-off, the company announced last month. The spin-off is expected to close in January 2027.

Trinzic will work as an independent, publicly traded company focused on technology and engineering services for the space and national security sector. KBR will remain a separate publicly traded company that will focus on sustainable technology and services to support the energy transition.

This is the salary required to live comfortably in Texas in 2026

Money Matters

A new national report looking at the income it takes to live comfortably in each of the 50 states has revealed Texans need to earn slightly less now than a year ago.

SmartAsset analyzed what a single individual, as well as family of four, must earn to cover minimum basic needs adjusted using the 50/30/20 budgeting rule. The resulting estimate represents the annual, pre-tax income needed to live comfortably in every U.S. state.

A single, full-time worker needs to make $90,563 to live comfortably in the Lone Star State, the report found, which is down a meager 0.2 percent from last year ($90,771).

Under the 50/30/20 budgeting strategy, that means a single Texas earner would have $45,282 to spend on necessities like housing and utilities, $27,169 for discretionary spending, and $18,113 for emergencies or retirement savings.

Texas ranked 34th nationally in SmartAsset's list of states with the highest income needed for a single adult to live "in sustainable comfort" in 2026. Only five other states — Tennessee, Maryland, Louisiana, North Carolina, and Mississippi — saw a decline in the income needed to live comfortably this year.

For a family of four to live comfortably in Texas, income requirements change significantly, according to the findings. To support a two-child household, a family needs $203,424 in combined total household income to be considered financially stable. This is down slightly from 2025, when SmartAsset reported a family of four in needed $204,922 to live comfortably in Texas.

This is a comfortable lifestyle for a family of four in Texas, according to the report:

  • $101,712 dedicated to necessities and living expenses
  • $61,027 dedicated to discretionary spending
  • $40,685 dedicated to emergencies, savings, or debt repaymen

According to the report, a family of four now needs to make at least $200,000 to live comfortably in 40 U.S. states, a figure that is far out of reach for many American families.

"As housing, grocery, transportation and other essential costs pressure household budgets, earning a six-figure salary no longer guarantees financial comfort in much of the U.S.," the report said. "A single adult now needs at least $80,000 a year to live comfortably in every state, while the threshold exceeds $100,000 in nearly half of states. For a family of four, the income needed to live comfortably is as much as $329,000."

Still, earning the minimum income to live comfortably in Texas doesn't guarantee financial stability in the Lone Star State's major cities. Earlier this year, SmartAsset determined single residents in Houston need to make about $90,000 to qualify as financially stable, while families of four need around $205,000.

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This article originally appeared on CultureMap.com.

Texas is the 7th hardest working state in America for 2026, says report

Labor Day Report

Texans pride themselves on being industrious, and a new report has confirmed Texas as one of the 10 most hardworking states in America in 2026.

The Lone Star State claimed the No. 7 spot this year in a slight dip from its 2025 ranking, where it appeared in the top five. Texas last ranked 7th in 2024, but the state has consistently appeared among the top 10 for nearly a decade.

WalletHub determined the rankings after analyzing 10 "direct" and "indirect" work factors across all 50 states, and then graded each metric on a 100-point scale, where a score of 100 signified the "hardest working." Analysts then examined each state’s weighted average across all metrics to calculate its overall score and used the resulting scores to rank-order the states.

There was only a 10.32-point difference between Texas and South Dakota, who claimed the top spot as America's hardest working state in 2026 with a score of 64.59 out of a possible 100 points.

Texas ranked 6th nationally in the "direct" work factors category, which examined the following six metrics:

  • The state's average workweek hours.
  • Employment rates.
  • The share of households where no adults work.
  • The share of workers leaving vacation time unused.
  • The share of "engaged" workers — those that are "involved in, enthusiastic about, and committed to their work and workplace," as defined by Gallup.
  • The rate of "idle youth" — individuals aged 18-24 who are not currently enrolled in school, not working, and have no degree beyond a high school diploma or GED.

Texas ties with Louisiana for the second highest average workweek hours nationwide, with Alaska topping the list with the No. 1 longest workweeks in America. Alaska is the only state where workers clock in more than 40 hours per week at their jobs, with WalletHub reporting Alaskans work 41.4 hours on average weekly.

In the "indirect" work factors category — which encompassed workers' average commute times, the share of workers with multiple jobs, annual volunteer hours per resident, and the average leisure time spent per day — Texas ranked 36th nationwide.

Here's how WalletHub ranked Texas in three individual metrics:

  • No. 10 – Average commute times
  • No. 20 – Average leisure time spent per day
  • No. 30 – Employment rates

According to the World Economic Forum, Americans clock in about 1,800 hours at work per year on average, which is 468 more hours per year than workers in Germany. And many are leaving vacation time on the table, WalletHub says.

"Even when given the chance to take time off, many Americans won’t, as nearly half of workers don't expect to use all of their allotted vacation days," the report said. "It is possible to work hard without overdoing it, though. Hard work is key to success, and the residents of some states understand that better than others."

Hardest-Working States in America


The top 10 hardest working states in America in 2026 are:

  • No. 1 – South Dakota
  • No. 2 – North Dakota
  • No. 3 – Alaska
  • No. 4 – Hawaii
  • No. 5 – Wyoming
  • No. 6 – Nebraska
  • No. 7 – Texas
  • No. 8 – New Hampshire
  • No. 9 – Tennessee
  • No. 10 – Georgia
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This article originally appeared on CultureMap.com.

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