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 byMiguel 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 byMiguel 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 engineers develop breakthrough device to advance spinal cord treatment

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A team of Rice University engineers has developed an implantable probe over a hundred times smaller than the width of a hair that aims to help develop better treatments for spinal cord disease and injury.

Detailed in a recent study published in Cell Reports, the probe or sensor, known as spinalNET, is used to explore how neurons in the spinal cord process sensation and control movement, according to a statement from Rice. The research was supported by the National Institutes of Health, Rice, the California-based Salk Institute for Biological Studies, and the philanthropic Mary K. Chapman Foundation based in Oklahoma.

The soft and flexible sensor was used to record neuronal activity in freely moving mice with high resolution for multiple days. Historically, tracking this level of activity has been difficult for researchers because the spinal cord and its neurons move so much during normal activity, according to the team.

“We developed a tiny sensor, spinalNET, that records the electrical activity of spinal neurons as the subject performs normal activity without any restraint,” Yu Wu, a research scientist at Rice and lead author of the study said in a statement. “Being able to extract such knowledge is a first but important step to develop cures for millions of people suffering from spinal cord diseases.”

The team says that before now the spinal cord has been considered a "black box." But the device has already helped the team uncover new findings about the body's rhythmic motor patterns, which drive walking, breathing and chewing.

Lan Luan (from left), Yu Wu, and Chong Xie are working on the breakthrough device. Photo by Jeff Fitlow/Rice University

"Some (spinal neurons) are strongly correlated with leg movement, but surprisingly, a lot of neurons have no obvious correlation with movement,” Wu said in the statement. “This indicates that the spinal circuit controlling rhythmic movement is more complicated than we thought.”

The team said they hope to explore these findings further and aim to use the technology for additional medical purposes.

“In addition to scientific insight, we believe that as the technology evolves, it has great potential as a medical device for people with spinal cord neurological disorders and injury,” Lan Luan, an associate professor of electrical and computer engineering at Rice and a corresponding author on the study, added in the statement.

Rice researchers have developed several implantable, minimally invasive devices to address health and mental health issues.

In the spring, the university announced that the United States Department of Defense had awarded a four-year, $7.8 million grant to the Texas Heart Institute and a Rice team led by co-investigator Yaxin Wang to continue to break ground on a novel left ventricular assist device (LVAD) that could be an alternative to current devices that prevent heart transplantation.

That same month, the university shared news that Professor Jacob Robinson had published findings on minimally invasive bioelectronics for treating psychiatric conditions. The 9-millimeter device can deliver precise and programmable stimulation to the brain to help treat depression, obsessive-compulsive disorder and post-traumatic stress disorder.

Houston clean hydrogen startup to pilot tech with O&G co.

stay gold

Gold H2, a Houston-based producer of clean hydrogen, is teaming up with a major U.S.-based oil and gas company as the first step in launching a 12-month series of pilot projects.

The tentative agreement with the unnamed oil and gas company kicks off the availability of the startup’s Black 2 Gold microbial technology. The technology underpins the startup’s biotech process for converting crude oil into proprietary Gold Hydrogen.

The cleantech startup plans to sign up several oil and gas companies for the pilot program. Gold H2 says it’s been in discussions with companies in North America, Latin America, India, Eastern Europe and the Middle East.

The pilot program is aimed at demonstrating how Gold H2’s technology can transform old oil wells into hydrogen-generating assets. Gold H2, a spinout of Houston-based biotech company Cemvita, says the technology is capable of producing hydrogen that’s cheaper and cleaner than ever before.

“This business model will reshape the traditional oil and gas industry landscape by further accelerating the clean energy transition and creating new economic opportunities in areas that were previously dismissed as unviable,” Gold H2 says in a news release.

The start of the Black 2 Gold demonstrations follows the recent hiring of oil and gas industry veteran Prabhdeep Singh Sekhon as CEO.

“With the proliferation of AI, growth of data centers, and a national boom in industrial manufacturing underway, affordable … carbon-free energy is more paramount than ever,” says Rayyan Islam, co-founder and general partner at venture capital firm 8090 Industries, an investor in Gold H2. “We’re investing in Gold H2, as we know they’ll play a pivotal role in unleashing a new dawn for energy abundance in partnership with the oil industry.”

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This article originally ran on EnergyCapital.

3 Houston innovators to know this week

who's who

Editor's note: Every week, I introduce you to a handful of Houston innovators to know recently making headlines with news of innovative technology, investment activity, and more. This week's batch includes an e-commerce startup founder, an industrial biologist, and a cellular scientist.

Omair Tariq, co-founder and CEO of Cart.com

Omair Tariq of Cart.com joins the Houston Innovators Podcast to share his confidence in Houston as the right place to scale his unicorn. Photo via Cart.com

Houston-based Cart.com, which operates a multichannel commerce platform, has secured $105 million in debt refinancing from investment manager BlackRock.

The debt refinancing follows a recent $25 million series C extension round, bringing Cart.com’s series C total to $85 million. The scaleup’s valuation now stands at $1.2 billion, making it one of the few $1 billion-plus “unicorns” in the Houston area.

Cart.com was co-founded by CEO Omair Tariq in October 2020. Read more.

Nádia Skorupa Parachin, vice president of industrial biotechnology at Cemvita

Nádia Skorupa Parachin joined Cemvita as vice president of industrial biotechnology. Photo courtesy of Cemvita

Houston-based biotech company Cemvita recently tapped two executives to help commercialize its sustainable fuel made from carbon waste.

Nádia Skorupa Parachin came aboard as vice president of industrial biotechnology, and Phil Garcia was promoted to vice president of commercialization.

Parachin most recently oversaw several projects at Boston-based biotech company Ginkjo Bioworks. She previously co-founded Brazilian biotech startup Integra Bioprocessos. Read more.

Han Xiao, associate professor of chemistry at Rice University

The funds were awarded to Han Xiao, a chemist at Rice University.

A Rice University chemist has landed a $2 million grant from the National Institute of Health for his work that aims to reprogram the genetic code and explore the role certain cells play in causing diseases like cancer and neurological disorders.

The funds were awarded to Han Xiao, the Norman Hackerman-Welch Young Investigator, associate professor of chemistry, from the NIH's Maximizing Investigators’ Research Award (MIRA) program, which supports medically focused laboratories. Xiao will use the five-year grant to advance his work on noncanonical amino acids.

“This innovative approach could revolutionize how we understand and control cellular functions,” Xiao said in the statement. Read more.

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