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.

------

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.)

------

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.

Ad Placement 300x100
Ad Placement 300x600

CultureMap Emails are Awesome

World's largest student startup competition names teams for 2025 Houston event

ready, set, pitch

The Rice Alliance for Technology and Entrepreneurship has announced the 42 student-led teams worldwide that will compete in the 25th annual Rice Business Plan Competition this spring.

The highly competitive event, known as one of the world’s largest and richest intercollegiate student startup challenges, will take place April 10–12 at Houston's The Ion. Teams in this year's competition represent 34 universities from four countries, including one team from Rice.

Graduate student-led teams from colleges or universities around the world will present their plans before more than 300 angel, venture capital, and corporate investors to compete for more than $1 million in prizes. Last year, top teams were awarded $1.5 million in investment and cash prizes.

The 2025 invitees include:

  • 3rd-i, University of Miami
  • AG3 Labs, Michigan State University
  • Arcticedge Technologies, University of Waterloo
  • Ark Health, University of Chicago
  • Automatic AI, University of Mississippi and University of New Orleans
  • Bobica Bars, Rowan University
  • Carbon Salary, Washington University in St. Louis
  • Carmine Minerals, California State University, San Bernardino
  • Celal-Mex, Monterrey Institute of Technology and Higher Education
  • CELLECT Laboratories, University of Waterloo
  • ECHO Solutions, University of Houston
  • EDUrain, University of Missouri-St. Louis
  • Eutrobac, University of California, Santa Cruz
  • FarmSmart.ai, Louisiana State University
  • Fetal Therapy Technologies, Johns Hopkins University
  • GreenLIB Materials, University of Ottawa
  • Humimic Biosystems, University of Arkansas
  • HydroHaul, Harvard University
  • Intero Biosystems, University of Michigan
  • Interplay, University of Missouri-Kansas City
  • MabLab, Harvard University
  • Microvitality, Tufts University
  • Mito Robotics, Carnegie Mellon University
  • Motmot, Michigan State University
  • Mud Rat, University of Connecticut
  • Nanoborne, University of Texas at Austin
  • NerView Surgical, McMaster University
  • NeuroFore, Washington University in St. Louis
  • Novus, Stanford University
  • OAQ, University of Toronto
  • Parthian Baattery Solutions, Columbia University
  • Pattern Materials, Rice University
  • Photon Queue, University of Illinois, Urbana-Champaign
  • re.solution, RWTH Aachen University
  • Rise Media, Yale University
  • Rivulet, University of Cambridge and Dartmouth College
  • Sabana, Carnegie Mellon University
  • SearchOwl, Case Western Reserve University
  • Six Carbons, Indiana University
  • Songscription, Stanford University
  • Watermarked.ai, University of Illinois, Urbana-Champaign
  • Xatoms, University of Toronto

This year's group joins more than 868 RBPC alums that have raised more than $6.1 billion in capital with 59 successful exits, according to the Rice Alliance.

Last year, Harvard's MesaQuantum, which was developing accurate and precise chip-scale clocks, took home the biggest sum of $335,000. While not named as a finalist, the team secured the most funding across a few prizes.

Protein Pints, a high-protein, low-sugar ice cream product from Michigan State University, won first place and the $150,000 GOOSE Capital Investment Grand Prize, as well as other prizes, bringing its total to $251,000.

Tesla recalling more than 375,000 vehicles due to power steering issue

Tesla Talk

Tesla is recalling more than 375,000 vehicles due to a power steering issue.

The recall is for certain 2023 Model 3 and Model Y vehicles operating software prior to 2023.38.4, according to the National Highway Traffic Safety Administration.

The printed circuit board for the electronic power steering assist may become overstressed, causing a loss of power steering assist when the vehicle reaches a stop and then accelerates again, the agency said.

The loss of power could required more effort to control the car by drivers, particularly at low speeds, increasing the risk of a crash.

Tesla isn't aware of any crashes, injuries, or deaths related to the condition.

The electric vehicle maker headed by Elon Musk has released a free software update to address the issue.

Letters are expected to be sent to vehicle owners on March 25. Owners may contact Tesla customer service at 1-877-798-3752 or the NHTSA at 1-888-327-4236.

Houston space tech companies land $25 million from Texas commission

Out Of This World

Two Houston aerospace companies have collectively received $25 million in grants from the Texas Space Commission.

Starlab Space picked up a $15 million grant, and Intuitive Machines gained a $10 million grant, according to a Space Commission news release.

Starlab Space says the money will help it develop the Systems Integration Lab in Webster, which will feature two components — the main lab and a software verification facility. The integration lab will aid creation of Starlab’s commercial space station.

“To ensure the success of our future space missions, we are starting with state-of-the-art testing facilities that will include the closest approximation to the flight environment as possible and allow us to verify requirements and validate the design of the Starlab space station,” Starlab CEO Tim Kopra said in a news release.

Starlab’s grant comes on top of a $217.5 million award from NASA to help eventually transition activity from the soon-to-be-retired International Space Station to new commercial destinations.

Intuitive Machines is a space exploration, infrastructure and services company. Among its projects are a lunar lander designed to land on the moon and a lunar rover designed for astronauts to travel on the moon’s surface.

The grants come from the Space Commission’s Space Exploration and Aeronautics Research Fund, which recently awarded $47.7 million to Texas companies.

Other recipients were:

  • Cedar Park-based Firefly Aerospace, which received $8.2 million
  • Brownsville-based Space Exploration Technologies (SpaceX), which received $7.5 million
  • Van Horn-based Blue Origin, which received $7 million

Gwen Griffin, chair of the commission, says the grants “will support Texas companies as we grow commercial, military, and civil aerospace activity across the state.”

State lawmakers established the commission in 2023, along with the Texas Aerospace Research & Space Economy Consortium, to bolster the state’s space industry.