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

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

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

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

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

The expectations of B2B vs. B2C

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

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

Data differences with B2B

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

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

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

Enhancing data capture in B2B analysis

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

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

B2B data integration challenges

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

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

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

Leveraging B2B data analysis for growth

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

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

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

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

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

Houston research: Why you need a data management plan

Houston voices

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

Error

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

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

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

Repositories

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

Integrity

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

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

Replication

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

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

That's so meta

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

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

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

The Big Idea

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

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

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

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

Houston voices

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

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

Take inventory

Is your data…

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

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

Check first

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

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

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

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

Consistent questions that DMPs ask include:

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

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

Pre-proposal

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

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

Post-project

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

Start out strong

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

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

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Houston falls from top 50 in global ranking of 'World's Best Cities'

Rankings & Reports

Houston is no longer one of the top 50 best cities in the world, according to a prestigious annual report by Canada-based real estate and tourism marketing firm Resonance Consultancy.

The newest "World's Best Cities" list dropped Houston from No. 40 last year to No. 58 for 2026.

The experts at Resonance Consultancy annually compare the world's top 100 cities with metropolitan populations of at least 1 million residents or more based on the relative qualities of livability, "lovability," and prosperity. The firm additionally collaborated with AI software company AlphaGeo to determine each city's "exposure to risk, adaptation capacity," and resilience to change.

The No. 1 best city in the world is London, with New York (No. 2), Paris (No. 3), Tokyo (No. 4), and Madrid (No. 5) rounding out the top five in 2026.

Houston at least didn't rank as poorly as it did in 2023, when the city surprisingly plummeted as the 66th best city in the world. In 2022, Houston ranked 42nd on the list.

Despite dropping 18 places, Resonance Consultancy maintains that Houston "keeps defying gravity" and is a "coveted hometown for the best and brightest on earth."

The report cited the Houston metro's ever-growing population, its relatively low median home values ($265,000 in 2024), and its expanding job market as top reasons for why the city shouldn't be overlooked.

"Chevron’s shift of its headquarters from California to Houston, backed by $100 million in renovations, crowns relocations drawn by record 2024 Port Houston throughput of more than four million containers and a projected 71,000 new jobs in 2025," the report said.

The report also draws attention to the city's diversity, spanning from the upcoming grand opening of the long-awaited Ismaili Center, to the transformation of several industrial buildings near Memorial City Mall into a mixed-use development called Greenside.

"West Houston’s Greenside will convert 35,000 square feet of warehouses into a retail, restaurant and community hub around a one-acre park by 2026, while America’s inaugural Ismaili Center remains on schedule for later this year," the report said. "The gathering place for the community and home for programs promoting understanding of Islam and the Ismaili community is another cultural jewel for the country’s most proudly diverse major city."

In Resonance Consultancy's separate list ranking "America's Best Cities," Houston fell out of the top 10 and currently ranks as the 13th best U.S. city.

Elsewhere in Texas, Austin and Dallas also saw major declines in their standings for 2026. Austin plummeted from No. 53 last year to No. 87 for 2026, and Dallas fell from No. 53 to No. 78.

"In this decade of rapid transformation, the world’s cities are confronting challenges head‑on, from climate resilience and aging infrastructure to equitable growth," the report said. "The pandemic, long forgotten but still a sage oracle, exposed foundational weaknesses – from health‑care capacity to housing affordability. Yet, true to their dynamic nature, the leading cities are not merely recovering, but setting the pace, defining new paradigms of innovation, sustainability and everyday livability."

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This article originally appeared on CultureMap.com.

Waymo self-driving robotaxis will launch in Houston in 2026

Coming Soon

Houston just cleared a major lane to the future. Waymo has announced the official launch of its self-driving robotaxi service in the Bayou City, beginning with employee-only operations this fall ahead of a public launch in early 2026.

The full rollout will include three Texas cities, Houston, Dallas, and San Antonio, along with Miami and Orlando, Florida. Currently, the company operates in the San Francisco Bay Area, Phoenix, and Los Angeles, with service available in Austin and Atlanta through Uber.

Before letting its technology loose on a city, Waymo first tests the routes with human drivers. Once each locale is mapped, the cars can begin driving independently. Unique situations are flagged by specialists, and engineers evaluate performance in virtual replicas of each city.

“Waymo’s quickly entering a number of new cities in the U.S. and around the world, and our approach to every new city is consistent,” explained the announcement. “We compare our driving performance against a proven baseline to validate the performance of the Waymo Driver and identify any unique local characteristics.”

The launch puts Waymo ahead of Tesla. Elon Musk’s Austin-based carmaker has made a lot of hullabaloo about autonomy being the future of the company, but has yet to launch its service on a wide scale.

Waymo started testing San Antonio’s roadways in May as part of a multi-city “road trip,” which also included Houston. The company says its measured approach to launches helps alleviate local concern over safety and other issues.

“The future of transportation is accelerating, and we are driving it forward with a commitment to quality and safety,” Waymo wrote. “Our rigorous process of continuous iteration, validation, and local engagement ensures that we put communities first as we expand.”

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This article originally appeared on CultureMap.com.

Shipley Donuts launches AI-powered ordering assistant

fresh tech

Popular Houston-born doughnut chain Shipley Donuts has added a first-of-its-kind AI-powered assistant to its online ordering platform.

The new assistant can create personalized order recommendations based on individual or group preferences, according to a news release from the company. Unlike standard chatbox features, the new assistant makes custom recommendations based on multiple customer factors, including budgetary habits, individual flavor preferences and order size.

"We're not just adding AI for the sake of innovation — we're solving real customer pain points by making ordering more intuitive, personalized and efficient," Kerry Leo, Shipley Vice President of Technology, said in the release.

The system also works for larger events, as it can make individual orders and catering recommendations for corporate events and meetings by suggesting quantities and assortments based on group size, event type and budget.

According to Shipley, nearly 1 in 4 guests have completed orders with the new AI technology since it launched on its website.

“The integration of the AI ordering assistant into our refreshed website represents a significant leap forward in how restaurant brands can leverage technology to enhance the customer experience,” Leo added in the release.

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