Tag Archives: Consumer Behavior Consumer Research

Las Vegas Formula One

Successful Innovation, Learning Experience or Total Disaster?

GUEST POST from Pete Foley

In Las Vegas, we are now clearing up after the Formula 1 Grand Prix on the Strip.  This extremely complex event required a great deal of executional innovation, and one that I think as innovators, we can learn quite a lot from. 

It was certainly a bumpy ride, both for the multi-million dollar Ferrari that hit an errant drain cover during practice, but also with respect to broader preparation, logistics, pricing and projections of consumer behavior.  Despite this, race itself was exciting and largely issue free, and even won over some of the most skeptical drivers.  In terms of Kahneman’s peak-end effects, there were both memorable lows, but also a triumphant end result.   So did this ultimately amount to success?

Success?:   For now, I think it very much depends upon your perspective and who you talk to.  Perhaps it’s a sign of the times, but in Las Vegas, the race was extremely polarizing, with often heated debates between pro- and anti- F1-ers that were often as competitive as the race.

The reality is that it will be months, or more likely years before the dust settles, and we know the answer.  And I strongly suspect that even then, those who are for and against it will all likely be able to claim support for their point of view.  One insight I think innovators can take from this is that success can be quite subjective in of itself, and greatly depends upon what factors you measure, what period of time you measure over, and often your ingoing biases.  And the bigger and more complex the innovation, often the harder it is to define and measure success.  

Compromise Effects:  When you launch a new product, it is often simpler and cheaper to measure its success narrowly in terms of specific dollar contribution to your business. But this often misses its holistic impact.   Premium products can elevate an entire category or brand, while poorly executed innovations can do the opposite.  For example, the compromise effect from Behavioral Economics suggests that a premium addition to a brand line up can shift the ‘Good, Better, Best’ spectrum of a category upwards.  This can boost dollar sales across a line up, even if the new premium product itself has only moderate sales.   For example, the addition of high priced wines to a menu can often increase the average dollars per bottle spent by diners, even if the expensive wine itself doesn’t sell.  The expensive wines shift the ‘safe middle’ of the consideration set upwards, and thus increase revenue, and hopefully profit.      

Money, Scope and Intangibles:  In the case of F1, how far can and should we cast the net when trying to measure success?  Can we look just at the bottom line?  Did this specific weekend bring in more than the same weekend the previous year in sports betting, rooms and entertainment?  Did that difference exceed the investments? 

Or is that too narrow?  What about the $$ impact on the weeks surrounding the event?  We know that some people stayed away because of the construction and congestion in the lead up to the race.  That should probably be added into, or subtracted from the equation. 

And then there’s the ‘who won and who lost question’? The benefits and losses were certainly not homogeneous across stakeholders.  The big casinos benefited disproportionately in comparison to the smaller restaurants that lost business due to construction, some to a degree that almost rivaled Covid.  Gig workers also fared differently. I have friends who gained business from the event, and friends who lost.  Many Uber drivers simply gave up and stopped working. But those who stayed, or the high-end limo drivers likely had bumper weekends.   Entertainers working shows that were disrupted by F1 lost out, but the plethora of special events that came with F1 also provided a major uptick in business for many performers and entertainers.

There is also substantial public investment to consider.  Somewhat bizarrely, the contribution of public funds was not agreed prior to the race, and the public-private cost sharing of tens of millions is still being negotiated.  But even facing that moving target, did increased (or decreased) tax income before, during and after the race offset those still to be determined costs?

Intangibles:  And then there’s the intangibles.  While Vegas is not exactly an unknown entity, F1 certainly upped its exposure, or in marketing terms, it’s mental availability.   It brought Vegas into the news, but was that in a positive or negative light?  Or is all publicity good publicity in this context? News coverage was mixed, with a lot of negative focus on the logistic issues, but also global coverage of what was generally regarded as an exciting race.   And of course, that media coverage also by definition marketed other businesses, including the spectacular Sphere. 

Logistics:  Traffic has been a nightmare with many who work on the strip facing unprecedented delays in their commutes for many weeks, with many commutes going from minutes to hours.   This reached a point where casinos were raffling substantial prizes, including a Tesla, just to persuade people to not call in sick.  Longer term, it’s hard to determine the impact on employee morale and retention, but its hard to imagine that it will be zero, and that brings costs of its own that go well beyond a raffled Tesla

Measuring Success?  In conclusion, this was a huge operation, and its impact by definition is going to be multidimensional.  The outcome was, not surprisingly, a mixed bag.  It could have been a lot better, or a lot worse. And even as the dust settles, it’s likely that different groups will be able to cherry pick data to support their current opinions and biases. 

Innovation Insights:  So what are some of the more generalized innovation insights we can draw?

(a) Innovation is rarely a one and done process.   We rarely get it right first time, and the bigger and more complex an innovation is, the more we usually have to learn.  F1 is the poster child for this, and the organization is going to have an enormous amount of data to plough through. The value of this will greatly depend on F1’s internal innovation culture.  Is it a learning organization?  In a situation like this, where billions of dollars, and careers are on the line, will it be open or defensive?  Great innovation organizations mostly put defensiveness aside, actively learn from mistakes, and adopt Devils Advocate approaches to learn from hard earned data. But culture is deeply embedded, and difficult to change, so much depends on the current culture of the organizations involved.  

(b) Going Fast versus Going Slow:  This project moved very, very quickly.  Turning a city like Las Vegas from scratch into a top of the line race track in less than a year was a massive challenge.  The upside is that if you go fast, you learn fast.  And the complexity of the task meant much of the insight could pragmatically only be achieved ‘on the ground’.  But conversely, better scenario planning might have helped anticipate some of the biggest issues, especially around traffic disruption, loss of business to smaller organizations, commuting issues and community outreach.  And things like not finalizing public-private contracts prior to execution will likely end up prolonging the agony.  Whatever our innovation is, big or small, hitting that sweet spot between winging it and over-thinking is key. 

(c) Understanding Real Consumer Behavior.  The casinos got pricing horribly wrong.  When the race was announced, hotel prices and race packages for the F1 weekend went through the roof.  But in the final run up to the race, prices for both rooms and the race itself plummeted.  One news article reported a hotel room on the strip as low as $18!  Tickets for the race that the previous month had cost $1600 had dropped to $800 or less on race day.  Visitors who had earlier paid top dollar for rooms were reported to be cancelling and rebooking, while those locked into rates were frustrated.  There is even a major lawsuit in progress around a cancelled practice.  I don’t know any details around how pricing was researched, and predicting the market for a new product or innovation is always a challenge.  In addition, the bigger the innovation, the more challenging the prediction game is, as there are less relevant anchors for consumers or the business to work from.   But I think the generalizable lesson for all innovators is to be humble.  Assume you don’t know, that your models are approximate, do as much research as you can in contexts that are a close to realistic as possible, don’t squeeze margins based on unrealistic expectations for the accuracy of business models, and build as much agility into innovation launches as possible.  Easier said than done I know, but one of the most consistent reasons for new product failure is over confidence in understanding real consumer response when the rubber hits the road (pun intended), and how it can differ from articulated consumer response derived in unrealistic contexts. Focus groups and on-line surveys can be quite misleading when it comes down to the reality of handing over hard cash, opportunity cost, or how we value ur precious time short versus long-term term.

Conclusion: Full disclosure, I’ve personally gone through the full spectrum with Formula One in Vegas.  I loved the idea when it was announced, but 6 months of construction, disruption, and the prospect of another two months of tear down have severely dented my enthusiasm.  Ultimately I went from coveting tickets to avoiding the event altogether.  People I know range from ecstatic to furious, and everything in between.  Did I mention it was polarizing? 

The reality is that this is an ongoing innovation process.   There is a 3-year contract with options to extend to 10 years.  How successful it ultimately is will likely be very dependent upon how good a learning and innovation culture Formula One and its partners are, or can become.  It’s a steep and expensive learning curve, and how it moves forward is going to be interesting if nothing else.  And being Vegas, we have both CES and the Super Bowl to distract us in the next few months, before we start preparing again for next year. 

Image credits: Pexels

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Exploring Cognitive Dissonance

Leveraging Consumer Behavior for Innovative Solutions

Exploring Cognitive Dissonance: Leveraging Consumer Behavior for Innovative Solutions

GUEST POST from Art Inteligencia

Cognitive dissonance is a psychological phenomenon that occurs when individuals experience conflicting beliefs, attitudes, or behaviors. This discomfort can lead to consumers making irrational decisions, which creates a unique opportunity for businesses to leverage this cognitive dissonance to drive innovation and create value for their customers.

Case Study 1: Apple Inc.

Apple has been a pioneer in leveraging cognitive dissonance to drive consumer behavior and innovation. For example, when Apple first introduced the iPhone, many consumers were initially resistant to the idea of switching from their traditional flip phones to a smartphone. However, Apple strategically marketed the iPhone as a revolutionary device that would simplify their lives and enhance their productivity. This created a cognitive dissonance in consumers who were torn between their reluctance to change and their desire to embrace new technology.

To address this cognitive dissonance, Apple focused on creating a seamless user experience with the iPhone, making it intuitive and easy to use. They also incorporated innovative features such as the App Store and Siri, which further incentivized consumers to adopt the iPhone. By understanding and leveraging consumers’ conflicting beliefs and attitudes, Apple was able to successfully drive adoption of the iPhone and revolutionize the smartphone industry.

Case Study 2: Tesla Inc.

Tesla is another company that has successfully leveraged cognitive dissonance to drive consumer behavior and innovation. When Tesla first introduced electric vehicles to the market, many consumers were skeptical about the feasibility and practicality of electric cars. There was a cognitive dissonance between consumers’ desire for environmentally-friendly transportation and their concerns about range anxiety and charging infrastructure.

To address this cognitive dissonance, Tesla focused on designing electric vehicles that not only were environmentally-friendly but also offered impressive performance and range. They also invested heavily in building out their Supercharger network, which made it easier for consumers to charge their electric vehicles while on the go. By addressing consumers’ concerns and offering innovative solutions, Tesla was able to disrupt the automotive industry and pioneer the shift towards electric vehicles.

Conclusion

Cognitive dissonance offers a unique opportunity for businesses to drive innovation and create value for their customers. By understanding and leveraging consumers’ conflicting beliefs, attitudes, and behaviors, companies can develop products and services that address their needs and desires. As demonstrated by Apple and Tesla, embracing cognitive dissonance can lead to breakthrough innovations and competitive advantages in the marketplace. By incorporating these insights into their strategic planning and marketing efforts, businesses can stay ahead of the curve and drive growth in an increasingly complex and competitive environment.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Pixabay

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The Power of Social Proof

How Consumer Behavior Influences Innovation Success

Title: The Power of Social Proof: How Consumer Behavior Influences Innovation Success

GUEST POST from Art Inteligencia

In today’s competitive marketplace, successful innovation is crucial for businesses to thrive and survive. However, understanding consumer behavior and leveraging social proof can significantly influence the success of these innovative endeavors. In this thought leadership article, we explore the concept of social proof and its impact on innovation success through two compelling case studies.

Case Study 1: Airbnb and the Power of Peer Recommendations:

In the past decade, the emergence of the sharing economy has disrupted traditional industries, particularly the hospitality sector. Airbnb, as a prime example, revolutionized the way people find accommodations by capitalizing on the power of social proof.

By allowing hosts and guests to leave reviews and ratings, Airbnb created a robust system of peer recommendations. This social proof effectively influenced potential customers’ decisions, leading to increased reservations and higher customer satisfaction rates. The number of positive reviews and the overall rating of properties became a key factor in the success or failure of hosts within the platform.

Airbnb’s innovative business model showcased the power of leveraging social proof to drive innovation success. By tapping into the collective wisdom of its users, Airbnb created a community-driven platform that thrived due to the trust established through social recommendations.

Case Study 2: Tesla and Consumer Influence on Electric Vehicles:

The success of electric vehicles (EVs) is another fascinating example of how consumer behavior and social proof contribute to innovation success. Tesla Motors, under the leadership of Elon Musk, pioneered the mass-market adoption of EVs and disrupted the automotive industry’s status quo.

One of the key factors behind Tesla’s success was its ability to tap into social proof to mitigate common consumer concerns about EVs. By producing high-quality vehicles with exceptional performance and range, Tesla created an aspirational brand that symbolized success, innovation, and environmentally-friendly choices.

Moreover, Tesla’s decision to build a network of Supercharger stations worldwide addressed charging infrastructure worries, a crucial aspect of EV adoption. This strategy provided consumers with tangible proof that electric vehicles were a reliable and practical transportation option.

Tesla’s innovative approach not only increased mainstream acceptance of EVs but also encouraged other automakers to invest in electric vehicle technologies. Consumer demand and social proof played a pivotal role in driving innovation within the automotive industry.

Conclusion

The power of social proof, as demonstrated through the case studies of Airbnb and Tesla, cannot be underestimated when it comes to innovation success. By understanding consumer behavior and influencing their choices through peer recommendations, businesses can gain a competitive edge and create new markets.

In today’s interconnected digital landscape, social proof plays a vital role in shaping consumer decision-making. Capitalizing on this power can help businesses drive innovation, boost customer trust, and achieve sustainable growth.

The lessons learned from Airbnb and Tesla reaffirm that by prioritizing social proof and incorporating consumer insights into the innovation process, organizations can create products and services that meet real consumer needs. As we move forward, businesses that can effectively harness the influence of consumer behavior and social proof will position themselves for long-term success in an ever-evolving marketplace.

Bottom line: Understanding trends is not quite the same thing as understanding the future, but trends are a component of futurology. Trend hunters use a formal approach to achieve their outcomes, but a methodology and tools like those in FutureHacking™ can empower anyone to be their own futurist and trend hunter.

Image credit: Unsplash

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