What might retail and restaurant brands learn from tens of thousands of first-party U.S. mobile consumers who not only have been GeoValidated^® as their customers, but whose profiles fit the specific consumer types the brand considers most important to understand?

Building a custom panel of profiled, known visitors makes it possible to conduct plug-and-play tracking studies in which the questionnaire can be repeated for each wave of customized, non-duplicated consumer panelists.

In one case, a client who customized its audience saved time and money by designing and fielding its own tracking study on MFourDIY^®, the only all-mobile DIYsurvey-building platform. The opportunity for accurate segmentation is a key feature: as new members sign up for the consumer panel that participates via MFour’s Surveys On The Go^® mobile research app, those who fit the required profiles are automatically funneled into the custom panel, ensuring ongoing representation and consistency for the tracking study. 

Over time, the client in question has seen completion rates of 80%, and drop-off rates under 2% from respondents who fit its consumer profiles and have been geolocated in one of its locations. The tracker focuses on questions about lifestyle and attitudes that impact how its validated customers view eating and health. Among the findings: 

• 60% of respondents agreed completely or very strongly that “the state of my health is largely in my control." 

• 25% stated agreed completely or strongly that “I consider myself to be fit and in shape.” 17% said just the opposite. ”

• Life is hectic out there: 40% of respondents agreed completely or strongly that “I’m always busy and on the go.” Only 8% were completely or strongly certain that “busy and on the go” does not describe their lifestyle. 

• The accelerated speed of life often dictates decisions about meals: 36% strongly or completely agreed that they opt for speed even though they feel that on-the-go restaurant meals can be unhealthy.

• Consumers want to fill up when they eat out, with 40% of respondents agreeing strongly or completely that good value depends on “more food for the money.” 

• At the opposite end of the spectrum, only 7% were convinced that quantity is not essential to good value in restaurant food.

• When it comes to where the rubber meets the road – or the meal meets the mouth  – a substantial majority of the client's validated customers confessed that they sometimes put pleasure over discipline: the statement, “I love rewarding myself with indulgent food or beverages,” elicited strong or complete agreement from 42% of participants, and an additional 36% said they were “somewhat” in agreement that they love indulging themselves.  

• Just 9% of respondents indicated a strong or complete rejection of indulging themselves when they eat.To that 9% we can only say, “well, if you’re not going to eat those fries, just pass them over to us.”

Can market researchers score special consumer insights by watching people who watch the Super Bowl? Answers may lie in the already observed behaviors of validated, first-party consumers on the days of two recent buzzed-about football games. These big days for football fans coincided with big days for carry-out pizza.

Major quick-serve pizza brands feasted on two key game days: the Monday, Nov. 19 pro football contest between Kansas City and Los Angeles, which attracted 16.7 million viewers, according to Nielsen, and the Monday, Jan. 7 college football championship between Clemson and Alabama, seen by 24.3 million.

To see how delicious these two Mondays were for pizza-sellers, we checked mobile location data available on MFour’s Path-2-Purchase™ Platform. It’s collected by observing the daily journeys of first-party mobile consumers across more than 12.5 million U.S. retail and restaurant locations. Brands get a unique opportunity to watch fluctuations in the ongoing visitation patterns of these validated, pre-profiled members of the largest all-mobile consumer panel. Observed participants have opted in to have their daily journeys tracked via their smartphones. The data shows not only where they go, but how often, on which days of the week, which times of day, and how long they stay. Valuable in itself, location data becomes even more useful when it’s used as a segmentation tool that identifies just the right people to approach for a subsequent survey.

In our glance at pizza consumption on the days of the two big Monday football telecasts, we looked at visits to Domino’s Pizza, Little Caesars and Pizza Hut.

• On the day of the celebrated, high-scoring game between Kansas City and LA, who both had league-best 9-1 records when they met, the three pizza chains enjoyed a combined 7% increase in visits above their average Monday. 

• The only other Monday that saw a bigger gain was Dec. 24 – Christmas Eve, when tracked consumers’ visits to the three pizza chains were 11% above the Monday average.

• The Jan. 7 college championship game saw combined visits to the three pizza outlets rise 5.5% above the average Monday. 

• Pizza Hut was the biggest beneficiary, scoring 11% above its average Monday visitation on each of the two big Monday game days.

• Domino’s was up 7% for the Monday night pro game and 3% for the college championship.

• Little Caesars saw game-day gains of 4% and 2%, respectively.

Armed with this location data, researchers would gain an advantage in exploring questions such as these:

Should competing QSR categories attempt counter-measures to maximize their own share of takeout orders on big sports-viewing days other than the Super Bowl?

Should advertisers consider using special, football-themed creative content and timed ad buys to take advantage of specific games that have a special buzz about them?

Answering these questions, and many others, requires direct input from consumers. What you lean by observing where they go will position you to identify exactly the right consumers for a mobile survey focused on the motivations behind those journeys.

For example, did a person who’d never been observed at a Pizza Hut stop at one on the evening of a big game? Why? Anything to do with watching the game? And how satisfied was this consumer with the experience of buying and eating Pizza Hut’s food?  

The odds of coming away with valuable insights improve drastically when you can first observe validated, pre-profiled consumers’ journeys to locations relevant to the research project at hand, and then survey the same consumers to discover the “why” behind the buy.

Think of this opportunity in football terms. Winning teams need the right personnel, and strong communication to develop a game plan and carry it out on the field. To win in today’s market research, observing location journeys lets you identify the right personnel – the consumers whose visits and demographic profiles identify them as the people you most want to know more about. Having identified the respondents you need, you communicate with them via a mobile survey to find out what motivates them, and how they experience shopping for and consuming a product.

Does this sound like a playbook for supplying relevant and reliable data and providing decision-makers with analysis and recommendations grounded in proven reality? For a hands-on experience, you can play with the free Path-2-Purchase demo tool by clicking here.

Gas stations are perhaps the most common ground for American consumers. The U.S. was home to 222 million licensed drivers as of 2016, according to the Census Bureau. They all need to buy gas, and any brand on the market will take them where they need to go.

However, gasoline consumers’ income can have a big impact on where they buy. There is a gap between ARCO, known for low prices and for not accepting credit cards, and Costco, which also features low prices, but requires a $60 membership fee.

• During the 90-day stretch from early June through Labor Day, consumers who earned less than $35,000 per year accounted for 49% of ARCO stations’ traffic.

• The same income bracket made up just 27% of Costco’s gasoline business.

• At the other end of the income spectrum, Costco drew 37% of its gasoline business from consumers earning $75,000 or more.

• Only 18% of ARCO’s visits during the summer driving season came from people whose household incomes topped $75,000.

It’s not just a matter of price differential. According to a report from Business Insider, Costco was the least expensive gasoline option, per gallon, in 17 states. And in California, which has the greatest number of ARCO stations, anecdotal evidence suggests that Costco competes well on price, although there are far more ARCO stations – six times as many in the Los Angeles DMA, for example.

• How heavily does that $60 membership fee figure into Costco’s consumer profiles?

• Is the membership fee the biggest hurdle keeping lower-income drivers from making Costco their brand?

• Or, for drivers in DMAs where ARCO and Costco compete, is the convenience of having more stations available a stronger factor in lower-income drivers' preference for ARCO?

The data on gas station visits, and on who those visitors are based on income, age and many more demographic characteristics, comes instantly into view for users of MFour’s Path-2-Purchase^® Platform. You’ll observe and track the daily journeys of validated, first-party consumer panel members who have opted in to participate in location-based research.

Knowing precisely who they are, and exactly where they go, gives you unprecedented opportunities to identify in an instant the population segments you need to study and understand.

But Path-2-Purchase^® isn’t just for collecting data from known audiences. It takes you a step further by arming you with instant data visualizations that help you identify new, research-relevant audiences to approach, and new questions to ask.

Studies based on Path-2-Purchase^® segmentation and targeting will get you fast responses from real consumers whose characteristics you’ll know before you even field your survey. You’ll come away with a real understanding based on observing and talking to real people who'll tell you the "why" behind the observational data you already have.

With the launch of Path-2-Purchase^® you finally have a choice. You can continue to depend on third-party data and settle for inferences and assumptions rather than direct knowledge as to who consumers actually are and what really motivates them. Or step up to validated, first-party opinions that reveal the motivations and emotions of actual, carefully-profiled mobile consumers. 

There’s lots more to explore on your way to premium data and high-octane consumer insights that dispense with inferences and put you in touch with direct reality.  To check out the Path-2-Purchase^® dashboard, just click here. And for a productive discussion about how the platform can power your projects’ specific needs, get in touch by clicking here.

Football season is back (yessss!!), and with it comes a tip for consumer insights pros: one of the key performance indicators for a market research team’s success is how well it can intercept consumers during their natural buying journeys.

In the NFL, interceptions are often game-changers, and it takes a rare combination of talent and skill to intercept. The key attributes are quickness and anticipation, and an uncanny knack for being in just the right position when the ball is in the air.

Quickness and being in the right place at the right time are also crucial to collecting quality consumer data that will give decision-making stakeholders the field position they need to advance their companies’ or brands’ marketing and sales goals.

In theory, retailers can get reliable (albeit seldom timely) data on what’s actually being bought. But they get no real insight into customers' motivations – the "why" behind the "what." The problem becomes exponentially harder when the subject is non-buying behavior. Who entered a store but failed to buy everything they’d intended to purchase? What did they not buy? Why did it happen, and how much revenue did the store leave on the table?

The answers, and the ability to defend against non-buying, won’t be forthcoming unless customer experience research teams learn how to intercept.

There’s no better way to collect premium data than by intercepting it from consumers naturally, and in real time, as they go about their daily buying journeys. So in the spirit of NFL players poring over game film to get a competitive edge, let’s look at a case study that illustrates how natural intercepts work.

The Problem: Researchers for a leading retail chain that does a huge volume in CPG sales were trying to tackle one of their business’s most frustrating problems: losing revenue because many customers who entered a store didn't buy everything they had intended to purchase.

The Answer: For the retail chain in question, all it took was a discussion with MFour reps about GeoValidation^® – a proprietary capability driven by the advanced GPS technology embedded in the Surveys on the Go^® research app. Clients track app-using U.S. consumers’ movements and verify when they arrive and then leave a location of research interest.

• In this case, all members of MFour’s first-party consumer panel who entered one of the client’s stores were located on arrival, and received a push notification of a survey opportunity upon departure.

• When they responded – with a 25% response rate within an hour and 50% within 24 hours – the process of intercept followed by data return was complete.

• Qualifiers for the study were 400 consumers nationwide, who said they had not purchased everything they had intended to buy.

• In beauty products, 31% of non-purchasers cited price as the factor that discouraged them from buying; 37% said they had simply been unable to find the item they wanted, or that it was not available.

• For shoppers looking for personal care products, 31% cited price and 28% cited unavailability or inability to find the intended item.

• Among candy and snack intenders, 20% said they didn’t buy because of pricing, and 24% because what they wanted wasn’t there or couldn’t be found.

• Among grocery and beverage shoppers who said they had left without an item they had arrived intending to purchase, 44% cited price and 24% said items were not available or couldn’t be found.

• Asked whether they were satisfied with their overall shopping experience, 57% of non-buyers rated their visit as an 8 or a 9 on a nine-point satisfaction scale. 24% graded their experience in the poor to middling range (1 to 6 on the scale).

The study gave the client clarity on factors that were costing it millions in revenue each day nationwide, and potentially alienating many customers. The previously unobtainable data from natural intercepts gave researchers their first clearly-informed look at the problem, so they could recommend a game plan to win back the sales and revenue that the chain’s stores were letting slide through their hands.

For an informative and productive conversation about how to program natural intercepts into your research game plan, just click here.