WELCOME TO OUR BLOG!

The posts here represent the opinions of CMB employees and guests—not necessarily the company as a whole. 

Subscribe to Email Updates

BROWSE BY TAG

see all

Robo-Advisors Aren't Your Father's Financial Advisor

Posted by Lori Vellucci

Tue, Dec 12, 2017

Back in the day, if you had a little money to invest, you called up the brokerage firm that your dad used, you talked to his“guy” and you asked him to invest your money for you. Those days aren’t totally gone, but over the last few years new technology has disrupted the traditional investor-client relationship—resulting in more ways than ever to invest your money yourself.

We all remember the iconic E*TRADE baby from way back in 2013. E*TRADE’s campaign brought the online discount stock brokerage firm for self-directed investors model into the mainstream. Since then, more DIY investment platforms have cropped up, each vying for the modern self-directed investor’s business. But one important learning from the DIY trend of the past decade is that even though this model lends itself to independent investing, DIY-investors still need some type of investment help.

Robo-advisors: The rise of AI in finance

The first robo-advisor was released in 2008 to help these new investors make smart money choices. For the most part, early DIY investors didn’t have a formal finance background, so robo-advisors offered them portfolio management services and insights that were once reserved for high-net-worth individuals—at a fraction of what a traditional human financial advisor might charge. It was a gamechanger.

Robo-advisor technology continues to shape the financial services industry with big players like Charles Schwab and Ameritrade each launching their own in the last few years. This growing interest and investment in robo-advisory technology is great for DIY investors and offers a ton of opportunity for traditional financial firms be on the cutting edge of FinTech.

Given the changing landscape, we wanted a better understanding of investor perceptions of robo-advisor clients.  Through our 2017 Consumer Pulse, we surveyed 2,000 US adults about FinTech, traditional financial services firms, and who they perceived as the technologies' typical user.

Who's using robo-advisors?

Typical Robo-Advisor User.png

CMB’s AffinID (a measure of social identity’s influence on consumers) score for this FinTech offering indicate that while all three components of AffinID (clarity, relatability, and social desirability) could stand improvement within the investor community. Relatively speaking, relatability is weakest--people have a clear image of what the typical robo-advisor user is like and that image is socially desirable, but they don't view the typical user as part of their "tribe".

The inability of investors to relate to their image of the typical robo-advisor user sheds light on a potential roadblock. Robo-service providers targeting traditional investors might consider messaging that conveys a typical user more closely aligned with the “traditional investor image”.

What emotions are driving use?

We found that robo-advisor users themselves are driven by feelings of being smart, wise, and savvyefficient, practical, productive.  Inspiration and motivation are also key emotional drivers for robo-advisor services.

Emotions that drive robo-advisor usage2.png

Why does this matter? It tells us what brands looking to differentiate themselves in a crowded FinTech market could be doing to attract more customers. These emotional drivers could be important messaging elements for those companies looking to court new money from traditional investors.

Are robo-advisors the next "big thing" in FinTech?

FinTech adoption curve2.png

Three quarters of robo-advisor users consider themselves early adopters, this is in contrast with users of mobile wallet and online-only banking--two technologies that have entered the mainstream. As traditional financial service providers make considerable investments in driving robo-advisor adoption, our findings show that to drive adoption it's critical to understand both how consumers want to feel, and how they perceive and relate to their image of the typical user.

Interested in learning more?

Our comprehensive FinTech study also looked at online-only investment apps, online-only banking, and mobile wallets. Download a sneak peek of our findings from all four in our Facing the FinTech Future series:

Topics: financial services research, Identity, AffinID, Artificial Intelligence, BrandFx

I, for one, welcome our new robot...partners

Posted by Laura Dulude

Tue, Oct 17, 2017

 

iStock-841217582.jpg

Ask a market researcher why they chose their career, and you won't hear them talk about prepping sample files, cleaning data, creating tables, and transferring those tables into a report. These tasks are all important parts of creating accurate and compelling deliverables, but the real value and fun is deriving insights, finding the story, and connecting that story to meaningful decisions.

So, what’s a researcher with a ton of data and not a lot of time to do? Hello, automation!

Automation is awesome.

There are a ton of examples of automation in market research, but for these purposes I'll keep it simple. As a data manager at CMB, part of my job is to proofread banner tables and reports, ensuring that the custom deliverables we provide to clients are 100% correct and consistent. I love digging through data, but let’s be honest, proofing isn’t the most exciting part of my role. Worse than a little monotony is that proofing done by a human is prone to human error.

To save time and avoid error, I use Excel formulas to compare two data lists and automatically flag any inaccuracies. This is much more accurate and quicker than checking lists against one another manually—it also means less eye strain.

As I said, this is a really simple example of automation, but even this use case is an incredible way to increase efficiency so I have more time to focus on finding meaning in the data.

Other examples include:

  • Reformatting tables for easier report population using Excel formulas
  • Creating Excel macros using VBA
  • SPSS loops and macros

I’m a huge proponent of automation, whether in the examples above or in myriad more complex scenarios. Automation helps us cut out inefficiencies and gives us time to focus on the cool stuff

Automation without human oversight? Not awesome.

Okay, so my proofreading example is quite basic because it doesn’t account for:

  • Correctness of labels
  • Ensuring all response options in a question are being reported on
  • Noting any reporting thresholds (e.g. only show items above 5%, only show items where this segment is significantly higher than 3+ other segments, etc.)
  • Visual consistency of the tables or report
  • Other details that come together to create a truly beautiful, accurate, and informative deliverable.

Some of the bullet points above can also be automated (e.g. thresholds for reporting and correctness of labels), but others can’t. On top of that, automation is also prone to human error—we can automate incorrectly by misaligning the data points or filtering and/or weighting the data incorrectly. Therefore, it’s imperative that, even after I automate, I review to catch any errors—flawless proofing requires a human touch.

When harnessed correctly, automation maximizes efficiency, alleviates tediousness, and reduces error to free up more time for insights. Before you start arming yourself against a robot takeover, remember: insights are an art and a science, and machines haven’t taken over the world just yet.

Topics: quantitative research, Artificial Intelligence, Market research Automation,

AI, AI, AI! What next?

Posted by Brant Cruz

Wed, May 31, 2017

robots.jpgPeople who know me are well aware I occasionally like to spin a tall tale. The routine is standard: I start with a barely believable premise, and if I see someone taking the bait, I keep adding ridiculous layers until my mark finally figures it out.

The other day started in similar fashion. Chris Neal (a colleague of mine) and I were asked by another colleague if our Silicon Valley clients were chanting this article’s mantra, “Mobile First to AI First.”  The real answer isn’t a simple “yes” or “no” (more on that in a bit). But in addition to answering the question, I decided to spin one of my famous yarns. I won’t bore you with the details, but the yarn evolved into me admitting that I was about to strike rich from investing in an MIT start-up that created AI-based robot leggings. Further, I’d sport those leggings while running the 2018 Boston Marathon as a publicity stunt.

I’m 5’9” (on a tall day) and 275 lbs. (after 24 hours of fasting). 

My only hesitation (according to the story) was that my wife was concerned my heart wouldn’t make it beyond the first mile and was greedily reviewing the details of my life insurance policy. 

Note: When my colleague reads this blog post, it will be the first time he or she realizes I was only pulling his/her leg. 

For the last few days, I’ve been basking in the satisfaction that only those with my genetic mutation feel. But that reflection has made me think–is my tale really that tall? The truth is, while neither Chris nor I hear “AI First” as universally and consistently cited as “Mobile First” was five years ago, AI is permeating strategy discussions at all major tech companies as they become more focused on the business opportunity it represents.

And, a lot of them are struggling to answer key questions. Where does AI “live” organizationally? Does it deserve its own category of products/apps, or should it remain a concept that permeates nearly every project across departments? Other challenges include foundational questions like who has subject matter expertise to advise on insights in this category adequately, and how can we market something this new (and to some, scary) effectively to the right audiences in a way that is compelling and easy to understand?

In my own experience, I can say that many consumers are ready for the realization of AI. Based on our recent work with Anki for their amazing robot Cozmo, consumers in millions of US HHs are excited to use AI in everything from fun to productivity. And, related to my colleague’s enthusiasm for my fictitious running suit, consumers in 8.8 million US households strongly agree with the statement “Tech toys/gadgets/robots make me feel closer to the future I’ve envisioned”.Cozmo Lifestyle 002-1.jpg

We’re also wrapping up a self-funded research study examining the barriers to and opportunities for getting coveted groups like Millennial and Gen Z to use Intelligent Personal Assistants (IPA—think Siri). Needless to say, AI is no longer a peripheral concept—it’s very much on the minds of consumers and brands alike. If you aren’t already, subscribe to our blog so you don’t miss a series of AI-inspired blog articles once we release our study’s findings.

In this context, I guess my MIT “get rich” story really wasn’t too far from believability. It’s possible that engineers at Nike or Under Armour are measuring up some other husky market researcher for a set of robotic leggings for some incredible athletic feat. Regardless, I’m excited about the possibilities–though my tastes tend more towards self-driving lawn mowers. 

Brant is CMB’s ecommerce and Digital Media Practice Leader, and will be co-presenting the aforementioned work with Anki at the Insights Association Northwest Educational Summit in San Francisco on June 8. In his near-future spare time he can be found hiding under his desk, avoiding his previously unsuspecting colleague. 

Are you registered for the Northwest Educational Summit on June 8 in San Francisco? If so, click here to receive our latest webinar and connect with one of our lead researchers.

Not going but still interested in learning about how Anki leverages emotions and identity to adapt, innovate, grow, and stay consumer-centric? Click here!

Topics: growth and innovation, Artificial Intelligence