By accounting for both known and unknowable factors, managers can identify salespeople with traits that work best in different types of sales. Getty Images

When you're a manager, decisions barrage you each day. What product works? Which store layout entices? How will you balance the budget? Many of these decisions ultimately hinge on one factor: the skills of your sales force.

Often, when managers evaluate their salespeople they contend with invisible factors that may not show up in commissions or name-tagged sales rosters — intangibles such as product placement, season or simply a store's surrounding population. This makes it hard to fully evaluate a salesperson, or to spot which workers can teach valuable skills to their peers and improve the whole team.

But what if you could plug a few variables into a statistical model to spot your best sellers? You could then ask the star salespeople to teach coworkers some of their secrets. New research by Rice Business professor Wagner A. Kamakura and colleague Danny P. Claro of Brazil's Insper Education and Research Institute offers a technique for doing this. Blending statistical methods that incorporate both known and unknown factors, Kamakura and Claro developed a practical tool that, for the first time, allows managers to identify staffers with key hidden skills.

To test their model, the researchers analyzed store data from 35 cosmetic and healthcare retail franchises in four South American markets. These particular stores were ideal to test the model because their salespeople were individually responsible for each transaction from the moment a customer entered a store to the time of purchase. The salespeople were also required to have detailed knowledge of products throughout each store.

Breaking down the product lines into 11 specific categories, and accounting for predictors such as commission, product display, time of year and market potential, Kamakura and Claro documented and compared each salesperson's performance across products and over time.

They then organized members of the salesforce by strengths and weaknesses, spotlighting those workers who used best practices in a certain area and those who might benefit from that savvy. The resulting insight allowed managers to name team members as either growth advisors or learners. Thanks to the model's detail, Kamakura and Claro note, managers can spot a salesperson who excels in one category but has room to learn, rather than seeing that worker averaged into a single, middle-of-the-pack ranking.

If a salesperson is, for example, a sales savant but lags in customer service, managers can use that insight to help the worker improve individually, while at the same time strategizing for the store's overall success. Put into practice, the model also allows managers to identify team members who excel at selling one specific product category — and encourage them to share their secrets and methods with coworkers.

It might seem that teaching one employee to sell one more set of earbuds or one more lawn chair makes little difference. But applied consistently over time, such personalized product-specific improvement can change the face of a salesforce — and in the end, a whole business. A good manager uses all the tools available. Kamakura and Claro's model makes it possible for every employee on a sales team to be a potential coach for the rest.

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This story originally ran on Rice Business Wisdom.

Based on research from Wagner A. Kamakura, the Jesse H. Jones Professor of Marketing at Jones Graduate School of Business at Rice University.

Keeping on track with trends is crucial to growing and developing a relationship with your customers, these Rice University researchers found. Getty Images

Rice researcher delves into the importance of trendspotting in consumer behavior

Houston voices

Every business wants to read consumers' minds: what they love, what they hate. Even more, businesses crave to know about mass trends before they're visible to the naked eye.

In the past, analysts searching for trends needed to pore over a vast range of sources for marketplace indicators. The internet and social media have changed that: marketers now have access to an avalanche of real-time indicators, laden with details about the wishes hidden within customers' hearts and minds. With services such as Trendistic (which tracks individual Twitter terms), Google Insights for Search and BlogPulse, modern marketers are even privy to the real-time conversations surrounding consumers' desires.

Now, imagine being able to analyze all this data across large panels of time – then distilling it so well that you could identify marketing trends quickly, accurately and quantitatively.

Rice Business professor Wagner A. Kamakura and Rex Y. Du of the University of Houston set out to create a model that makes this possible. Because both quantitative and qualitative trendspotting are exploratory endeavors, Kamakura notes, both types of research can yield results that are broad but also inaccurate. To remedy this, Kamakura and Du devised a new model for quickly and accurately refining market data into trend patterns.

Kamakura and Du's model entails taking five simple steps to analyze gathered data using a quantitative method. By following this process of refining the data tens or hundreds of times, then isolating the information into specific seasonal and non-seasonal trends or dynamic trends, researchers can generate steady trend patterns across time panels.

Here's the process:

  • First, gather individual indicators by assembling data from different sources, with the understanding that the information is interconnected. It's crucial to select the data methodically, rather than making random choices, in order to avoid subjectively preselecting irrelevant indicators and blocking out relevant ones. Done sloppily, this first step can generate misleading information.
  • Distill the data into a few common factors. The raw data might include inaccuracies, which must be filtered out to lower the risk of overreacting or noting erroneous indicators.
  • Interpret and identify common trends by understanding the causes of spikes or dips in consumer behavior. It's key to separate non-cyclical and cyclical changes, because exterior events such as holidays or weather can alter behavior.
  • Compare your analysis with previously identified trends and other variables to establish their validity and generate insights. Looking at past performance through the filter of new insights can offer managers important guidance.
  • Project the trend lines you've identified using historical tracking data and their modeling framework. These trend lines can then be extrapolated into near-future projections, allowing managers to better position themselves and be proactive trying to reverse unfavorable trends and leverage positive ones.

It's important to bear in mind that the indicators used for quantitative trendspotting are prone to random and systematic errors, Kamakura writes. The model he devised, however, can filter these errors because it keeps them from appearing across different series of time panels. The result: better ability to identify genuine movements and general trends, free from the influence of seasonal events and from random error.

It goes without saying that the information and persuasiveness offered by the internet are inevitably attended by noise. For marketers, this means that without filtering, some trends show spikes for temporary items – mere viral jolts that can skew market research.

Kamakura and Du's model helps sidestep this problem by blending available historical data analysis, large time panels and movements while avoiding errors common to more traditional methods. For managers longing to glimpse the next big thing, this analytical model can reveal emerging consumer movements with clarity – just as they're becoming the future.

(For the mathematically inclined, and those comfortable with Excel macros and Add-Ins, who want to try trendspotting on their own tracking data, Kamakura's Analytical Tools for Excel (KATE) can be downloaded for free at http://wak2.web.rice.edu/bio/Kamakura_Analytic_Tools.html.)

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This article originally appeared on Rice Business Wisdom.

Wagner A. Kamakura is Jesse H. Jones Professor of Marketing at Jones Graduate School of Business at Rice University.

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AI-powered Houston startup helps restaurants boost customer loyalty

order up

It’s no secret that restaurant trends move fast and margins run thin. And with the proliferation of platforms like Uber Eats, DoorDash and Easy Cater, customer loyalty is fleeting.

The solution?

How about an AI-powered restaurant technology platform that helps restaurant brands cut back on third-party platforms in favor of driving direct discovery, conversion and loyalty?

Enter Saivory. Founded in 2025 by Stephen Klein, a software investor, and Fajita Pete’s restaurateur Hugh Guill, the Houston-based startup aims to help eateries better understand and activate guest behavior across digital channels as AI increasingly reshapes how consumers discover and engage with brands.

In less than a year, Saivory has partnered with Shipley Do-Nuts and Fajita Pete’s to bring AI-powered ordering to life.

“With Saivory, we were able to answer the question of, ‘what if the ordering process could be reduced to a single step, where customers simply tell us what they want and AI takes care of the rest?’” Klein tells InnovationMap.

The Houston-based startup made such an immediate impact that it was selected as a semi-finalist during Start-Up Alley at MURTEC, the restaurant industry’s leading technology conference, which took place last month in Las Vegas.

“Houston is a great hub for technology innovation, and we were proud to represent the city at MURTEC this year,” says Klein. “We didn’t win, but we were able to talk about some of the work that we have existing in the market for clients right now and a little bit about what we’re working on in the future.”

In the current restaurant technology ecosystem, the third-party aggregators own the customer attention that brings volume to restaurants, while also taking big commissions and having control over the end relationships with the customer.

That can often make it difficult for restaurants to grow loyalty and repeat business from customers. Saivory aims to level the playing field for restaurants, helping them stay more connected to their customers.

Take Saivory’s recent application with Shipley’s Do-Nuts, for example.

Saivory powered the donut giant’s AI-ordering and launched Shipley's website and mobile app to support its over 300 locations in Texas alone.

Shipley’s new AI-powered assistant helps users create personalized order recommendations based on individual or group preferences. And unlike standard chatbox features, the new assistant makes custom recommendations based on multiple customer factors, including budgetary habits, individual flavor preferences and order size. It can also be used for large catering orders.

“They're seeing more traffic to the site and they're seeing when customers use our AI-enabled flows,” Klein says. “And they're seeing higher basket sizes, bigger tickets, by about 25 percent.”

Klein says Saivory’s technology helps strengthen first-party digital relationships, reduce friction and cart abandonment, improve average order value, and delivers personalized, efficient experiences.

“It’s a win-win: the customer gets the right order quickly, while the restaurant gets a bigger margin,” he adds.

Additionally, the technology makes it easier for restaurants to share rewards, loyalty and discounts, ultimately growing more direct traffic and making restaurants less reliant on third-party delivery apps.

Next up for Saivory is adding new components to its platform to enhance the relationship between restaurant and customer, as well as technology around making it easier for restaurants to get found on Google.

“A lot of people are still searching for the best donuts near me,” Klein says. “Or what’s the best Mexican food near me? Customers will increasingly move to AI, where they’re going to ask where they should eat dinner and expect it to just order them dinner. They will eventually expect the technology to know how to do that. So that’s what we’re driving at.”

Houston leads U.S. in population growth for 2025, Census says

Boomtown

Imagine that the Houston metro area swallowed a city the size of Pearland in just one year. That’s essentially what happened from 2024 to 2025, with the Houston metro ranking first in the U.S. for population growth based on the number of people.

New estimates from the U.S. Census Bureau show the 10-county Houston metro added 126,720 residents from July 1, 2024, to July 1, 2025. That’s just shy of Pearland’s roughly 133,000-resident tally.

To calculate population, the Census Bureau counts births, deaths, new residents, and moved-away residents.

Region’s population approaches 8 million

On July 1, 2025, the Houston metro’s population hovered slightly above 7.9 million, up 1.6 percent from the same time in 2024. In the very near future, the region’s population should break the eight million mark.

This follows massive growth in the past 20 years. From 2005 to 2025, the region’s population soared by 39 percent. By comparison, the growth rate from 2021 to 2025 sat at nine percent.

A forecast from the Texas Demographics Center indicates that under a middle-of-the-road scenario, the Houston metro’s population will reach nearly 8.5 million in mid-2030 and more than 9.5 million in mid-2040.

Dan Potter, director of Rice University’s Houston Population Research Center, attributes much of the region’s population surge to people moving to the area from outside the U.S. In Harris County, this means a combination of military personnel returning home, people living or working overseas coming back to the U.S., and immigrants relocating to the U.S., he tells CultureMap.

But Harris County fell short from 2024 to 2025 when it comes to people moving here from elsewhere in the U.S., according to Potter. Counties surrounding Harris County benefited from that trend, drawing new residents who preferred to settle in the suburbs.

“The incredible pull and attraction of the Houston area is its economy, its people, and its affordability, and the significant growth that was observed in 2024 and again in 2025 speaks to the magnetism of the region,” Potter says. “That pull to Houston is too strong to be turned off overnight.”

Cooling economy and immigration shifts slow down growth

Whether looking at urban or suburban places, population growth in the Houston area slowed in 2025 and appears to be slowing even more this year, Potter says.

“A cooling economy and changes to immigration policy are a one-two combination that could knock out the region’s population growth,” says Potter, citing the region’s addition of a less-than-expected 14,800 jobs in 2025 as an example.

Weaker population growth may not be felt evenly across the metro area, according to Potter.

A continuing influx of people from Houston to outlying counties such as Brazoria, Fort Bend, Liberty, Montgomery, and Waller could curb growth in Harris County, Potter said. Why? If the number of people arriving from other other countries flattens or even drops, then there could be “doughnut-style population growth for the next few years, where Harris County and Houston see declines while the suburban counties see an increase.”

Harris County represents 40 percent of region’s population lift

Houston-anchored Harris County accounted for almost 40 percent of the region’s population spike from 2024 to 2025. In one year, Harris County grew by 48,695 residents, or 1 percent, pushing its population past five million. That increase put Harris County in first place for numeric growth (rather than percentage growth) among all U.S. counties.

From 2020 to 2025, Harris County’s growth rate was 6.6 percent. It remains the country’s third largest county based on population, behind Southern California’s Los Angeles County and Illinois’ Chicago-anchored Cook County.

Harris County is on track to surpass Cook County in size in the near future. As of July 1, 2025, a nearly 150,000-resident gap separated population-losing Cook County and fast-growing Harris County.

The Texas Demographics Center predicts Harris County’s population will be 5.37 million in mid-2030 and just short of six million in mid-2040.

Suburban counties see significant population gains

Harris County isn’t the only county in the area that experienced a growth spurt from 2024 to 2025:

  • Waller County’s population climbed 5.69 percent, winding up at 69,858. Its growth rate ranked second among U.S. counties.
  • Liberty County’s population rose 4.4 percent to 121,364, putting its growth rate in eighth place among U.S. counties.
  • Montgomery County gained 30,011 residents, with its population landing at 781,194. That placed it at No. 4 among U.S. counties for numeric growth.
  • Fort Bend County picked up 24,163 residents, arriving at a total of 975,191 and positioning it at No. 8 among U.S. counties for numeric growth. Fort Bend County, the region’s second largest county based on population, is projected to break the one million-resident mark by July 2030, according to the Texas Demographics Center.

“Lower mortgage rates from 2009 to 2022 and the rise of remote work have made suburban housing more attractive, especially for families seeking affordability,” Pramod Sambidi, the Houston-Galveston Area Council’s assistant director of data analytics and research, said last year. “Additionally, suburban areas are seeing more multifamily developments than before the pandemic.”

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This article originally appeared on CultureMap.com.

5 Houston-area companies named among world's most innovative for 2026

In The Spotlight

Led by Conroe-based Hertha Metals, five organizations in the Houston area earned praise on Fast Company’s list of the World’s Most Innovative Companies of 2026.

Hertha Metals ranked No. 1 in the manufacturing category.

Last year, Hertha unveiled a single-step process for steelmaking that it says is cheaper, more energy-efficient and just as scalable as traditional steel manufacturing. It started testing the process in 2024 at a one-metric-ton-per-day pilot plant.

At the same time, Hertha announced more than $17 million in venture capital funding from investors such as Breakthrough Energy, Clean Energy Ventures, Khosla Ventures, and Pear VC.

“We’re not just reinventing steelmaking; we’re redefining what’s possible in materials, manufacturing, and national resilience,” Laureen Meroueh, founder and CEO of Hertha, said at the time.

Meroueh was also recently named to Inc. Magazine's 2026 Female Founders 500 list.

Hertha, founded in 2022, says traditional steelmaking relies on an outdated, coal-based multistep process that is costly, and contributes up to 9 percent of industrial energy use and 10 percent of global carbon emissions.

By contrast, Hertha’s method converts low-grade iron ore into molten steel or high-purity iron in one step. The company says its process is 30 percent more energy-efficient than traditional steelmaking and costs less than producing steel in China.

Last year, Hertha said it planned to break ground in 2026 on a plant capable of producing more than 9,000 metric tons of steel per year. In its next phase, the company plans to operate at 500,000 metric tons of steel production per year.

Here are Fast Company’s rankings for the four other Houston-area organizations:

  • Houston-based Vaulted Deep, No. 3 in catchall “other” category.
  • XGS Energy, No. 7 in the energy category. XGS’ proprietary solid-state geothermal system uses thermally conductive materials to deliver affordable energy anywhere hot rock is located. While Fast Company lists Houston as XGS’ headquarters, and the company has a major presence in the city, XGS is based in Palo Alto, California.
  • Houston-based residential real estate brokerage Epique Realty, No. 10 in the business services category. Epique, which bills itself as the industry’s first AI brokerage, provides a free AI toolkit for real estate agents to enhance marketing, streamline content creation, and improve engagement with clients and prospects.
  • Texas A&M University’s Nanostructured Materials Lab in College Station. The lab studies nano-structured materials to make materials lighter for the aerospace industry, improve energy storage, and enable the creation of “smart” textiles.
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This article first appeared on our sister site, EnergyCapitalHTX.com.