Marketing Darwinism - by Paul Dunay
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Marketing Darwinism - by Paul Dunay
Advertising, Big Data, Business Intelligence, Cloud, Data, Data Analytics, Data Mining, Innovation, Strategy

Real Estate, Real AI, Real Value

Submitted article by Romi Mahajan

Chief Commercial Officer, Quantarium

The world of technology is known as much for its hype as it is for its legitimate innovations.  Atone level, this is understandable. Dreamers can only accomplish big things when they dream big and followup on those dreams with supporting rhetoric. At a different level, however, it serves to dupe consumers, customers,and investors into alchemist fantasies that often defy the laws of physics.  What we need, naturally, is a balance.

With AI, and claims about it, we as a community have come to the point where we have to decide if we are okay with “fact-checking.”  Are all claims about AI fair and accurate?  Do all companies that claim to be “doing AI” pass muster in that regard? After all, haven’t many organizations referred to any and all of their “data”initiatives as AI? Have we diluted the term so as to make it meaningless?

Discerning investors have started to kick the AI tires.  Highly skilled Scientists and Engineers increasingly refuse to be beguiled by marketing claims, choosing instead to dig deeply into the code and methodologies surrounding its production before allowing themselves to be recruited by the countless organizations that seek the limited supply of talent. 

Perhaps more relevant, still, is that people in all roles ask one fundamental question:  “Is there any relevant and practical application to the AI work you are doing?”

On all these matters, Quantarium can hold its head high.  From “Real AI” to “Real Applications of AI,”Quantarium is altering and enhancing our notions of what is possible in residential real estate, the world’s single largest asset class.

Take for instance an important but mundane question, likely asked by millions of people every day.  “What is my house worth?”  Several pundits will offer several answers to this question, no doubt.  But, will the answers be accurate and in this case, what does accuracy even mean?  What data goes into the answer?  Do we have all the data we need?  Is it all available? Do the data we collect account for every single aspect of the house that could or should go into the valuation? 

Now take an extrapolation of this question with magnified scale.  Imagine you are the CEO of a large bank that “owns” half-a-million residential mortgages. What is your portfolio worth?  How much risk are you holding in the portfolio?  Are you too exposed in a particular geography or demographic?  Do you have sufficient data and the ability to process and make sense out of it?  Can you do this all with the speed that is called for by regulation and market conditions?

These questions are easy to pose but hard to answer.  Further, while these questions may not seem “sexy,” they underscore the reality of the single biggest source of economic value and for most families the single largest source of equity.  Using AI to drive accuracy, speed, and scale in this market is complex, genuine and incredibly important.Indeed, real AI applied to real industries with real outcomes is the name of the game. Therein lies the balance we seek, the convergence of both the hype and of the reality.

December 18, 2018by Paul Dunay
Artificial Intelligence, Big Data, Business Intelligence, Cloud, Data, Data Analytics, Data Mining, Innovation, Strategy

Interview with Clement Ifrim, CEO and Co-Founder, Quantarium

Marketing Darwinism: Clement, tell us about Quantarium.

Clement: The company is inspired by insights from Quantum Physics and the potential inherent in applying them to Machine Learning approaches within an A.I. framework. We have organically gathered the analytical methods of fields as far reaching as Quantitative Genetics to build a leading Artificial Intelligence company that enables competitive advantage in vertical industries via advanced predictive and propensity models along with smart decision-engines. To be sure, there remains a lot for Quantarium to accomplish and indeed we have the ambition to match, though we are quite proud of our synthesis to date and the benefits our customers are enjoying each day.

Marketing Darwinism: Can you tell us which verticals you focus on mostly?

Clement: The beauty and peril of A.I. is that it can seemingly apply to everything and that can be intoxicating, thus both market and organizational focus to execute become paramount. Our first salvo is residential Real Estate, a $20 Trillion asset class that represents in a meaningful personal perspective, the most important of all sectors because it constitutes the largest purchase a family ever makes. Quantarium looks at Real Estate from a perspective not only of Data (and there is a lot of Data!) but also of modeling scenarios of what “could” be. For both financial institutions that “own” and service mortgages and for the individuals who own homes, understanding the “deep” economics is very important. From valuations to other analytical models, Quantarium intends to revolutionize the approach and economics.

Marketing Darwinism: Clement, you have a background in large companies like Microsoft, how is it being a CEO of a start-up.

Clement: Thanks for the question. There is nothing headier than building something with world-class people who humble me every day with their vigor and intelligence. At Microsoft, I learned how to manage A+ teams and to think about products and customers at scale. Applying that to the need for speed in the startup world is my biggest challenge and joy.

Marketing Darwinism: Clement, I must ask you this. A.I. has become a “buzz phrase” …how do you distinguish yourself.

Clement: You are certainly correct about that. The technology business is very much about fashion and phraseology. Unfortunately, it is also often about false claims as well. Quantarium’s founders team, with Ph.D’s and accomplished experts in the field, undertook the approach that A.I. is best when it enhances the ability for people to both arrive at a valuable truth in a quicker and more judicious fashion, and then start to predict future truths, or certainties, given the current business exigencies. Quantarium established itself as an A.I. company from the get-go, it’s in our DNA; as a matter of fact, the first platform Quantarium built, QVM/Quantarium Valuation Model relied on M.L./A.I. technologies such as evolutionary programming when “Artificial Intelligence” was not such a buzz phrase yet. Our team consists not only of award winning Mathematicians and Engineers but also of some of the best “technology translators” in the industry. Algorithms and A.I. are indeed assets, however when you add them to the human agency and agility, you get real applications of real A.I.

Marketing Darwinism: What’s in store for Quantarium in the next phase of your growth?

Clement: Good question. While structured as a tridimensional growth approach, with a clear focus on increasing market share, innovation / differentiated I.P. and product expansion, in many ways we’ve been silent for too long. We enjoy genuine, solid relationships with our customers and partners but haven’t “splashed” in the market yet. That has been by design but the time has now come to shout from the rooftops. We’re showing up at conferences like the O’Reilly AI Summit and Strata. While we remain humble and true to ourselves, we are bold at the same time so watch out for us.


About Clement

Clement is Co-Founder and CEO of Quantarium, an Artificial Intelligence company enabling vertical industries via advanced Predictive and Analytic models, and smart decision-ing engines. As the name of the company suggests, inspired by Quantum Physics and fueled by the power and potential of Machine Learning such as synthesizing and leveraging approaches from Quantitative Genetics, towards resolving significant predictive challenges, Clement is an accomplished international professional for leveraging Data Science and A.I. as well as a proven business leader.

With degrees in Computer Science, Clement spent 14 years building large-scale and Enterprise-level software products and services in areas traversing Content Management and Enterprise Search. Responsible for strategy and product development, Clement directed enterprise teams for Microsoft such as SharePoint, and MS Enterprise Search, while building a proven track-record for recruiting and developing teams with exceptional culture. Prior to Microsoft, Clement started and ran several software companies.

Originally hailing from Romania, Clement lives in the Seattle-area with his wife and children. He is actively involved in a variety of philanthropies and applies philosophy to technology as he builds lasting companies.

August 14, 2018by Paul Dunay
Big Data, Data Mining

Getting Big Data to Actually Work

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Most marketers I talk with today say they are drowning in data. But in reality data they really want sits in disparate systems throughout the organization. Or if their company has invested big money in a traditional data warehouse, the results have fallen short of expectations. This is because traditional data warehouses were never designed to handle the volume, variety and velocity of today’s data-centric applications. So, while most marketers and most companies “talk” about big data they just go on with “business as usual” taking little or no action.

This is not just my opinion. Recently, my UK colleague, Richard Petley, director of PwC Risk and Assurance, conducted a survey of 1,800 senior business leaders in North America and Europe. And only a small percentage reported effective data management practices. 43 percent of companies surveyed “obtain little tangible benefit from their information,” while 23 percent “derive no benefit whatsoever,” according to the study. That means three quarters of organizations surveyed lack the skills and technology to use their data to gain an edge on competitors.

The problem is not access to data. It’s the management of it. What companies really need is the ability to manage large amounts of data in a safe, agile and adaptable fashion. And that means they need a more modern data warehouse.

The overall purpose of a data warehouse is to integrate corporate data from various internal and external sources. Implementing a data warehouse is traditionally a long, costly and risky process. When the solution is ready, it’s often slow, outdated and hard to update as business changes. A modern data warehouse is different – employing new technologies, products, and approaches. Approaches that allow for both speed and agility.

With a modern data warehouse, you only have to query one source to get the data you need. When you add automation to the mix, you can load, clean, integrate, and format the data in record time.

POSSIBLE is a creative agency that brings results-driven digital solutions to some of the world’s most dynamic brands. Every two weeks, analysts faced the herculean task of reporting campaign results based on 10 different data sources, applying 20 different measures on 70+ products delivered by 100+ media partners. They would spend on average 35 hours just processing data before they could begin analysis.

When I spoke to the POSSIBLE team they reported this free demo introduced them to a data warehouse automation tool from TimeXtender. After a surprisingly fast implementation period, the “data munging” performed by POSSIBLE’s analysts has now been reduced 68%. “This has really turned out to be a big win for us. The fact that we can now get actionable data to analysts so much faster allows us to spend more time providing valuable insights to clients,” says Harmony Crawford, Associate Director of Marketing Sciences.

As my colleague Richard Petley likes to say, “Data is the lifeblood of the digital economy.” It can provide insight, inform decisions and deepen relationships, and drive competitive advantage, but only if it’s managed in an agile and adaptable way.

So the next time you find yourself complaining about the problem with big data, stop talking and start researching the modern data warehouse and data warehouse automation.

March 31, 2016by Paul Dunay
Big Data, Data Analytics, Innovation, Social Business Intelligence

Social Data Made Simple: Getting Started with a Strategy

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Last week I moderated another Social Media Today webinar as part of their Best Thinker webinar series, this time on the topic of Social Data Made Simple: Getting Started with a Strategy. This webinar featured Ira Haberman (@irahaberman) Director of Storytelling at BrainRider, Ned Kumar (@nedkumar) Digital Strategist for FedEx and Sean Williams (@Colorado2NYC) Consumer Promotions Social Media at JetBlue Airlines. We discussed how to get started with a strategy around social data.

Here are three key takeaways from the webinar:

  1. Know your audience – with social data there are so many sources that one could get lost trying to pull it all together – start with the end in mind in regards to what audience you are trying to reach. Let that be your guide post for any decisions on data.
  2. Sentiment is better on a group than on a single post – Sean talked about how JetBlue tracks sentiment on a group of travelers (ex. travelers to the Northeast in a snow storm versus one tweet from a single traveler)
  3. Most important part of a data strategy – is to commit to having a strategy for your data. According to the panel that is most often overlooked.

To get a copy of the slides or to listen to the replay, please click here. You can also scan the highlights of this webinar on Twitter by reading the Storify below.

Our next webinar is titled Cultivating Creative Thinking for Customer Engagement; be sure to sign up for it or view the schedule of other upcoming webinars here.

August 1, 2015by Paul Dunay
Behavioral Targeting, Big Data, Customer Experience, eCommerce, Personalization

Using Big Data To Target The Right Consumers With The Right Offers

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Should every visitor to your website be treated the same? Should each customer see the exact same offers, options, products and pages?

The more forward-thinking online marketers recognize that “personalizing” each customer’s experience on their site can make a dramatic difference in ultimate sales, customer loyalty and long-term profitability of the business.

Fact is, in many markets, customers have actually come to expect individually tailored offers and experiences—based on who they are, what they’ve bought before or even how they have come to the site.

But exactly what should you personalize on the site? Which offers, products or promotions should you present to which customer? And how can you tell what each type of customer will respond to best?

When you know what you want to accomplish, you will be able to identify the right combination of technology, tools and strategy for personalizing each customer’s experience. Here is where to start:

Harness the Power of Big Data, Big Testing

The notion of big data holds great promise for finding ways to personalizing the Web experience for individual customers. The vast amounts of data on customer behavior and history that can be captured via the Web and be invaluable in making decisions about how the website should work, what customers respond to, and understanding the discrete segments in your customer base.

Marketers who can harness the power of big data will be able to make decisions based on evidence, rather than guesswork—giving them a distinct advantage over the competition.

Of course, making sense of huge volumes of data, which may be in different forms and come from different sources, is not so easy. What’s more, it’s also difficult to translate that information into “personalizations” that are meaningful and compelling to your customers.

That is where today’s more advanced tools come in.

The aggregation and use of big data are crucial to segmenting and targeting your individual customers with the appropriate experiences. It requires employing predictive behavioral targeting and optimization techniques to remove the complexity. Your systems need to make real-time digital decisions for the masses—anytime, anywhere.

Love Your Loyalty Programs

For most marketers, loyalty programs provide a wealth of personalized data on your most desirable customers. But once you’ve enrolled customers, what should you do with the data?

This data isn’t just for tracking points and past reservations. It can be used to digitally personalize the experience for each customer in real time. Initiatives like offers, promotions, calls to action, special prices—whether on your website, mobile site or app—can all be preselected or promoted based on each visitor’s unique profile. This tactic ensures visitors see content relevant only to their loyalty level and behavior. A better experience leads to higher loyalty.

With each loyalty program visitor who comes to your website comes their unique “virtual profile” that can—and should—be used to tailor their experience on your site, in real time. Insight on behaviors such as previous products researched, frequency of purchases, the nature of past purchases, and ads or offers they’ve clicked can inform what content and offers you should make available to each individual, and precisely when in the process.

Don’t Upsell or Cross-Sell Too Soon 

One mistake marketers often make is automatically tagging on extras, such as upsells, options or accessory products, as their customers enter the booking funnel. The customer who already had a price in mind suddenly sees that number increase just as it’s time to purchase. By forcing these add-ons at the wrong time, you’re more likely to elevate annoyance levels than average sales.

With recommendations, upselling and cross-selling, timing is everything. Don’t be pushy up front; instead, leverage CRM and personalization data to get the right offer in the customer’s face at the right moment.

Ditch the Rules; Get Automated

While rules-based targeting may work, it won’t get you very far when you’re trying to personalize offers for millions of site visitors. It is virtually impossible to manually create rules that can handle the thousands of combinations of behaviors, products and promotions, for every single person.

The next best option (and next big idea) is automated personalization solutions. Advanced predictive models can dynamically serve content and offers based on a user’s current and past online behavior. This way, your visitors will always have the most relevant and appropriate experience on home pages, landing pages, search engine results pages, the booking funnel and every page in between. In the case of repeat visitors to your site, for example, you might retarget them with an offer based on their last purchase, or their last search, all in real time.

Making sure these tools are on hand can ultimately help the business build consumer-centric promotional strategies.

Sync Your Channels

Your customers don’t think in channels; they think in brands. So they expect the same personalized experience they get on your site to be on their smartphones, in their email and even on Facebook. Customer experience is the number one ticket to prolonged brand loyalty and engagement.

How does your brand look across channels? Is it 100 percent consistent, optimized and personalized? If not, you could be missing a golden opportunity to improve hotel, call center, direct mail, social and mobile experiences. No matter where they visit you, your brand experience should be ready. Thanks to automated technologies, you can more accurately predict a customer’s next interest and follow up with optimized, targeted messaging, no matter how, or through which channel, they access your brand.

Combining this data with CRM data in real time to drive sales and customer retention is the future. CRM practices were born and bred in the offline world, but today marrying offline, online and mobile consumer data through new technologies can help you achieve better CRM and multichannel marketing outcomes: more precise targeting, personalization and consumer connections across all media channels, and delivered at the time most appropriate to increasing conversion—a very important factor in online marketing.

Imagine being able to target your consumers across the various phases of purchase with different messages at research, selection, shipping and the like. Not only can you dramatically enhance and personalize their experience with your brand, but increased retention, loyalty and customer lifetime values also result from a truly connected multichannel experience.

Remember, personalization isn’t just marketing hype. It’s a complex concept that really can live up to its billing. But first, marketers must identify what personalization really means in their business—and what it means to their objectives, target customers and buying cycles.

When it comes to their websites, mobile sites, apps, social media and CRM platforms, the online industry must realize that only through a customized combination of multivariate testing, optimization and personalization best practices can they truly begin to reach consumers with personalization that is effective and full of impact. There are no easy answers or instant solutions for creating personalization that works. It’s about evolution rather than revolution.

August 10, 2013by Paul Dunay
Behavioral Targeting, Customer Experience, eCommerce, Mobile, Social Media

10 Ecommerce Predictions for 2013

Thanks to smarter marketing, better technology and consumers speaking out, 2013 just might be the year we see a real shift in how close customers and companies can really get.

We know the deal—people are spending, and continuing to spend, more and more online. Every year, Cyber Monday will beat out the last. Mobile and tablet revenues will continue to increase. And bricks-and-mortar retailers will scramble to keep pace with a digitally driven world.

The truth is, consumers are demanding optimized and personalized sites to offer them a richer, more relevant online experience. It’s no longer an option for marketers—it’s a must-have. In 2013, expect to see:

  1. Testing (Finally) Becomes a Must-Have – Companies big and small have dabbled in this for a decade. But now, everyone has to get serious about it. Companies that don’t test won’t get anywhere near providing the best online experiences for their audience.
  2. True, Real-Time Personalization, for Everyone – Now that this complex technology is made easily available to the masses, we’re going to see major industries like finance, travel and media lead the charge—but also expect businesses in other industries, such as gaming and charity, to take advantage of personalization solutions to offer more custom experiences.
  3. Consumers Get Over the Privacy Debate – Because consumers are getting on board with personalization, they should expect to see more of the general information they share online used by companies. Everything from age, geography and life stage, incorporating social profiles (e.g., married versus single) will play a part in offering a more relevant, more valuable ecommerce experience.
  4. Retailers Start to Love Loyalty Programs – It’s not just for frequent fliers anymore. Now businesses across industries (retail, finance, etc.) are launching loyalty programs—and integrating data into comprehensive customer profiles—to offer the next level of personalization and service.
  5. Mobile Gets Personal Too – As consumers adapt to living their lives from their mobile phones and tablets, they’ll expect platform-specific offerings that offer a better shopping experience, geo-specific content, special offers and other elements that complement and enhance life on the go.
  6. Responsive Design as the Rule – A site that’s designed for optimal viewing no matter which mobile or tablet device is being used is the new norm. Gone are the days of resizing, scrolling and otherwise struggling to view a site depending on the size of your computer or device screen.
  7. The Rise of Cross-Channel Experiences – Consumers don’t think in channels, they think in brands. So a completely seamless ecommerce experience no matter where they are —at their desktops, on their smartphones and tablets, or on social pages and sites—is a must-have.
  8. Companies Get a Handle on Big Data – Most businesses have an abundance of useful data, however, very few are using this data to provide targeted individual experiences at the right time to respond to savvy consumers’ needs. In the coming year, expect to see more brands getting a handle on this to offer customers more targeted offers across all channels in real time.
  9. Social Media Grows Up – For far too long, marketers have treated social media as an island from the rest of their strategy—and, in turn, have not reaped any benefits of it being a useful sales tool. Going forward, we’ll see more brands using social data to personalize experiences on their websites, as well as applying testing and personalization to their own Facebook pages.
  10. B2B Catches Up to B2C  – When it comes to testing and personalization, consumer-facing businesses aren’t the only ones catching on. B2B companies—and their customers—crave a great online experience too.  More and more B2B sites will use testing and personalization to create well-optimized and targeted sites based on user behaviors.

As a consumer and a marketer, I’m looking forward to getting online in 2013.

 

January 16, 2013by Paul Dunay

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Welcome to my blog, my name is Paul Dunay and I lead Red Hat's Financial Services Marketing team Globally, I am also a Certified Professional Coach, Author and Award-Winning B2B Marketing Expert. Any views expressed are my own.

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