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
Applications, Big Data, Business Intelligence, Cloud, Digital Transformation, Innovation, Strategy

Interview with Joe Martin CEO of CloudFit Software and Kyle Wagner CFO of CloudFit Software

Marketing Darwinism: I’m very interested in CloudFit’s strategy. Can you tell our readers a bit more about it?

JM: Thanks Paul for your affirmation. CloudFit is in the “Managed Digital Transformation” space. What this means specifically is that Digital Transformation is very much a function of embracing the cloud and that migrating your applications and workloads to the cloud is not a “one and done” exercise. Cloud Migration as a concept has to be understand as both a set of generalizable principles but also as a very individual factor as each business has its own priorities and constraints. Our software and services accelerate this journey and allow customers to “migrate, monitor, and measure” their cloud applications.

Marketing Darwinism: Fascinating. So is this mostly about financial savings (since you mentioned acceleration?)

KW: It’s about operational excellence of which a piece is financial savings, a piece is accountability, and a piece is working in the background so that the organization can grow its core business and innovate versus getting all its energies caught up in the transformation itself. As a CFO I think about my peers and their needs but I also think about the roles of the CIO and CEO as they are charged with technology-enabled futures.

Marketing Darwinism: You two boast 4 decades of collective Microsoft experience and your three other Principals add another 4 decades. Wow! Tell me about that.

JM and KW: Microsoft has played a huge role in our collective learning and imagination. We are humbled to have been part of Microsoft’s journey to the forefront of Enterprise Computing, Cloud Services, and related areas. We are proud of the large scale we helped enable. Microsoft and its amazing people continue to be core partners and vectors for our success. Clearly, the customers are our main focus and at times they run hybrid or non-Microsoft environments. As a software and services company we have to both respect the customers’ needs but also remember where we came from!

Marketing Darwinism: You are a young company but have already done a major acquisition. That’s very ambitious. Am I reading this correctly?

JM: Paul thanks for this question. Yes, our acquisition of Composable Systems cemented both our team but also our ongoing and deep relationships with core customers. We are indeed young but are very hungry to add value and wanted to create a force multiplier early. We welcomed not only the revenue and customer streams but also the team and expertise.

KW: I’d like to add to this too. We all have had big company backgrounds as you know; I’ve also had the pleasure to help build one of the fastest growing technology companies in the Northwest and understand the importance of building the right team and equipping them with the right tools from the get-go. We didn’t start CloudFit to be a lifestyle business but instead of grow quickly as a function of our value-add.

Marketing Darwinism: What do your customers say about you?

JM: Paul, thanks for bringing it back to them. We get very favorable reviews from our customers, many of whom consider us as key partners in their Digital Transformation. In the earlier days, we had a few hiccups and we learned from these. We went in with confident humility and have improved our customer story, interaction, and value-delivery each and every day. We hope to continue to improve. But overall we feel very good about this area of our business.

Marketing Darwinism: What’s the “Garden-variety” case for someone to contact CloudFit?

KW and JM: We believe that any organization that knows they want to transform but needs to understand what the journey is and how to do it in a methodical and accountable way while accelerating time to value is a perfect conversation for us. We want to partner with all organizations that are entering this journey and need to connect their Business needs with this IT process. We believe that Managed Digital Transformation is a very large space and is where the puck is going.

September 26, 2018by Paul Dunay
Big Data, Cloud, Customer, Customer Experience, Data, Data Analytics, Data Mining, Enterprise 2.0, Innovation, Strategy

Interview with Samir Saluja, Co-Founder of DeriveOne

Marketing Darwinism caught up with Samir Saluja, Co-Founder of DeriveOne and former Microsoft Learning Executive.

Marketing Darwinism: Samir, you left Microsoft to start DeriveOne with your partner Jason Talwar. Tell us about that transition.

Samir:
Microsoft played a huge role in my development and in my understanding of the needs of customers. It also helped me understand the importance of data and using data for scale. What Jason and I realized is that despite the importance of data in the organizational and business world, most were not conceiving of it correctly or in the most efficient manner. We saw that “data for data’s sake” started becoming the essential mantra for companies and we wanted to help them avoid that trap. Thus we started DeriveOne. We consider Microsoft a key partner so still are in the ecosystem.

Marketing Darwinism: “Data for data’s sake?” What do you mean?

Samir: Data has come to be seen as an important commodity and as such companies are scrambling to ingest it and even hoard it. Ingestion is great but what about digestion? How do you use this data? What about data-overload? What about useless data? What about “fake” data? The point here is that data is not an unalloyed good if not trained on decisions. In fact, we believe you need to look at the decisions first and figure out the data needed based on the decisions not just because “data is good.”

Marketing Darwinism: You have a very varied background. Tell us more about your journey.

Samir: Thanks Paul. I have spent time in the Peace Corp, as an entrepreneur, as a business-owner, as a Microsoft employee and as a volunteer. All of these experiences helped me converge on being who I am today, personally and professionally. The Peace Corp helped me learn to listen, empathize and act. Being an entrepreneur taught me about risk and reward. Microsoft helped me understand the importance scaling through partnerships. DeriveOne has helped me realize the value of focus.

Marketing Darwinism: Why should an organization hire DeriveOne?

Samir: We believe that partnering with our customers in the context of what they need and what their customers need is crucial. We help organizations, medium to large and even some startups, use data to hone and focus their customer segmentation strategy, the cognitive diversity of their teams, and to inculcate the culture of decision-driven data. We believe that methodology matters, eliciting what the true decisions that need to be made is key, and delivering accountability is necessary. We are humbled daily by interest in our company.

September 19, 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
Applications, Big Data, Customer Experience, Data, Data Analytics, Data Mining, Innovation

Getting Towards a Mature Data Infrastructure

Data is the watchword in organizations large and small. In fact, how an organization frames data is the single most important determination of future success or failure. As some put it, Data is the new “oil,” the commodity of most value in the modern age.

Many business leaders understand this intuitively. As business-users in the organization are forced to make larger number of critical decisions with larger “payloads” on a more frequent basis, the idea that these decisions must be data-driven is at the fore. Gut instinct is fine but gut instinct inflected with timely, contextual, and comprehensive knowledge of relevant data is a winning strategy.

While the idea of being “data-driven” is fundamental and powerful, most organizations fall short. Intentions are necessary but not sufficient. For most organizations, the technology and operational infrastructure that defines their “data” is predicated on notions that made sense in an earlier era in which there were simply less sources of data and less change to existing sources. The “size” of the data question makes for a complexity that is not pre-defined and therefore the solution to the data problem has to be flexible and adaptive. Data infrastructure maturity is necessary in today’s business environment and has 4 basic qualities: Governance, Security, Agility, and Automation.

Without these 4 qualifiers, 2 core facets of the solution are absent- democratizing access to data and liberating IT from the backlog and fatigue associated with constantly-changing business needs. Business-users work in the “NOW” timeframe while IT has its own rhythms. In order to truly be data-driven in a way that scales, organizations must empower business-users while simultaneously freeing IT to innovate. While there are cultural hurdles to this state, the biggest blockers are infrastructural.

Until very recently, good enough was, alas, good enough. The internecine conflict between Business and IT was considered just a fact of life, a “cost of doing business.” With automation technology, business users’ data needs can be managed on the fly and without the need for reactive hand-coding, conferring agility to the business teams and handing time back to the IT teams to innovate and more resources from lower value tasks to higher value tasks. This structural win-win is available today and harmonizes the needs of Business and IT.

If data is the new oil then an infrastructure to capitalize on it is necessary- an infrastructure that is mature and “Hub”-like. While all organizations are different, they are similar in their data needs and the data platforms that win will accommodate diversity and change inherently.

Guest post by:
Romi Mahajan
Chief Commercial Officer, TimeXtender

March 6, 2017by 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

index

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
Advertising, Behavioral Targeting, Big Data, Branding, Content Marketing, Customer Experience, email Marketing, Inbound Marketing, Interactive Marketing, Lead Generation, Lead Nurturing, Personal Branding, Social Media, Strategy, Thought Leadership

4 Stages of a Thought Leadership Maturity Model

thought-leadership

Here is a great piece on the maturity of a company’s Thought Leadership program by ITSMA.

Last year I was asked by ITSMA to collaborate on this piece with them. They also tapped into companies like Deloitte, E&Y, IBM, Coginzant, SAP and more.

What came out is quite interesting for any company looking to take their thought leadership program to the next level. Here are a few points I pulled out to highlight for you that can help you make the case internally:

  • 79% of would-be buyers say thought leadership is important to critical to determining which providers they want to learn more about
  • 75% of would-be buyers say thought leadership helps them determine which buyers to put on their short list
  • Traditional format for thought leadership has been the white paper but in this era of digital and social that isn’t enough
  • To reap the benefits of a thought leadership program you must have SME’s that are recognized outside of your company
  • Interaction with SME’s in social media improves the ability to communicate key thought leadership ideas

Click here for a full copy of the report on the 4 Stages of a Thought Leadership Maturity Model

Enjoy!

July 1, 2015by Paul Dunay
Big Data, Content Marketing, Data Analytics, Interactive Marketing, Leadership, Listening, Monitoring, ROI, Social Media

Integrating Listening Into Your Platform for ROI

show-me-the-ROI-resized-600.jpeg

This week I moderated another Social Media Today webinar as part of their Best Thinker webinar series, this time on the topic of Way Beyond Listening: Integrating Listening Into Your Platform for ROI. This webinar was sponsored by Synthesio and featured Brian Melinat (@brianmelinat) Director of Marketing Analytics within Dell, Kristine Vick (@kristinevick) Principal in the Digital and Content team at SAS, and Ben Lapidus (@benlapidus) Senior Sales Engineer at Synthesio. We discussed nine ways companies have found to connect social media to revenue and ROI.

Here are nine ways to connect Social Media to Revenue and ultimately ROI

  1. Map your social activities to all 4 stages of a customer journey: Awareness, Acquisition, Activation and Retention
  2. Connect social media to all marketing campaigns to gauge response
  3. Connect social media to SEO activities to increase SEO
  4. Plot your social media sentiment against your NPS scores
  5. Provide delightful customer support
  6. Listen for Lead Gen opportunities
  7. Use social for new product ideas
  8. Use social media to vet pricing of new products
  9. Use social media for M&A ideas in your product lines

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 To LinkIn or Not to LinkIn: Getting Ahead of Your Competitors with Innovative Strategies; be sure to sign up for it or view the schedule of other upcoming webinars here.

 

June 10, 2015by Paul Dunay
Big Data, Business Intelligence, Innovation, Leadership

Why Sustainable Competitive Advantage is so 1990

Rita McGrath

I had a chance to catch up with Columbia Business School professor and fellow author, Rita McGrath to discuss her latest book called – The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business (Harvard Business Review Press, 2013). I also look forward to seeing her speak about this topic at the upcoming World Business Forum held in New York at Radio City Music Hall on October 7-8.

Tell us why sustainable competitive advantage really a failed notion these days?

Because it causes companies to do a lot of dysfunctional things like just focusing on the bottom line.  If you’re looking for things to stay the same and you’re looking for reasons to keep just doing what you’re doing every day, then chances are that you’re going to be taken by surprise by the changes in the environment or changes in the competitive intensity of your business or things that are just not going to take you in a positive direction.

So the assumption that change is the weird thing and stability is the normal thing is something that causes a lot of companies to get taken by surprise.  That’s why I argue that if you have this bias for sustainable (as in long-lasting, not as environmentally sustainable) it sets you up to make a lot of poor decisions in an environment that’s changing rapidly.

So how should companies think about and organize themselves to take advantage of short-term sustainable advantages?

The first big thing that companies need to do is to look at the elements of their business portfolio as an integrated whole, see that some things you’re doing that are driving today’s core business and that are going to continue to drive tomorrow’s core business.   And you should keep doing them.  Then you’ve got some things that you’re investing in which may be candidates to be part of the next generation core business, things that you’re doing today that could lead to a big, healthy business in the future.  When Apple – just to take a common example – goes from making computers to making music players, but that’s an investment in one of these new platforms.

Then you’ve got to have things that you’re working on that are what I call “options,” which are small investments you’re making today that buy you the right but not the obligation to make some kind of future investments or take advantage of some future opportunity but that you don’t necessarily have to follow through on.

What does “good” in this new age look like?

If you look in the book, there’s this set of ten growth outliers that I think get a lot of this right. The kinds of things that they’re good at doing are letting their structure change as their business opportunities change.  Things like making sure that leaders don’t get too calcified in any one role or any one spot.  Making sure that they do things fast, they make decisions quickly.  Their pace is quicker than a lot of other firms.

The problem with a lot of companies, particularly with respect to things like innovation, is that their structures were built to serve some of their business purpose in the past.  So the structure they have today was built to help deliver yesterday’s business.  When tomorrow’s business requires doing something different, you might need a different structure to go after it.  But very often, the phrase I hear all the time is it “falls between the cracks” of the existing business.  So what you want to be thinking about is building the right structure to deliver the business of the future.

What role can marketing play in helping to define a new opportunity?  Is it the classic role that marketing plays, or is it something more?

I think it’s something different, and I think the world of marketing is about to undergo the most ginormous upheaval.  And it has to do with the fact that on the one hand, the analytics that form the cornerstone of traditional marketing are really changing rapidly.  When I was doing my PhD, it was all about conjoint analysis and co-word grouping and feature-function maps.  Today with the advent of big data and the ability to combine data across many different, previous-unrelated databases, the onus on marketing to get really smart about how they use data and what discoveries they find from them is going to be very strong.  There’s going to be a huge amount of pressure for that.

So I’ll give you a specific example.  My colleague at Columbia, Oded Netzer did a big data project involving the use of the entire Edmunds database.  It was a big, involved study, but he was able to use social media mentions from the Edmunds database to identify the General Motors push to rebrand the Cadillac to be more in line with a European luxury car and less like an American family car, which is how many people were beginning to think of it.  He was able to demonstrate that that a particular set of investments actually got traction in the perception of the brand using only social media.  I think that’s totally different than a lot of the tools that are in the marketing toolkit today.

What could this mean for the average marketer’s career?  What does the ability to take advantage of these sorts of transient advantages mean for marketers?

I would suggest – don’t let yourself get stale.  My watchwords are – if you come to work every day and all you’re doing is coming to work every day, you’ve got a long-term problem!

Moreover you’ve really got to know what’s going on out there.  And I’ll give an example of a friend of mine at a big publishing company.  She’d been let go and was meeting with a friend of mine who runs the learning and development department of this particular company.  This marketing woman was saying I can’t get interviews.  Or if she got interviews, she didn’t get offers because they want to know about things like search engine optimization, big data, social, and she had never had to learn any of that stuff.  My friend meanwhile was completely outraged because she had arranged for online courses this woman could have taken advantage of, but she didn’t.  The woman just came to work and did her job.  As a consequence, she wasn’t even aware that a lot of this stuff was beginning to become a real for any company she considered going to.

So the point is I think you’d need to constantly be thinking about where are your skills in relationship to where the demand is going to be?  Are you learning new things?  Even if you don’t directly and immediately see the connection between your job and those skills, are you learning something new on a regular basis?

September 10, 2014by 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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