Marketing Darwinism - by Paul Dunay
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Home
Bio
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Speaking
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Podcasts
Photos
Awards
Abstracts
Testimonials
  • Home
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  • Webinars
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  • Podcasts
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  • Awards
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  • Testimonials
Marketing Darwinism - by Paul Dunay
Applications, Business Intelligence, Data Analytics, Marketing

Interview with Dharmesh Godha of Advaiya

Marketing Darwinism met up with Dharmesh Godha of Advaiya to see how the company is progressing and what their next “big bet” is on.

Marketing Darwinism:   Dharmesh, good to chat again.  I know you’ve done a lot with the company over the past several years; give us a refresher on who Advaiya is and what the company stands for.

Dharmesh:  Thanks Paul.  To start with, it’s worth mentioning our tagline here- “Making Technology Work.” While that might sound cliché, we find that the abundance of technology choices and methodologies of implementation actually can conspire to make it difficult for companies to make the optimal bets.  Further, technology by itself doesn’t solve problems, so we work hard to make customers’ technology choices work in their context and in a manner that most befits them. 

We started the company for this reason.  No doubt, along the way, we took some turns, hit a few dead-ends but also found a few amazing areas to focus on.  All companies evolve.  Interestingly, we have come full-circle to a real competency- helping companies digitize in their own contexts and without the orthodoxies often imposed by technology-forward perspectives that don’t recognize that there are multiple paths to success.

So that’s a long way to say that we stand for driving our customers’ growth and success in their own image not in some “perfect state.” We have found that that state doesn’t exist!

Marketing Darwinism: This sounds like “Digital Transformation”.  Is that what you focus on?

Dharmesh: Yes and no.  DT is an amazing phrase but it has come to mean too many things at once.  We look at things in a forward-yet-practical way- start with a particular need a company has- a baby step- and get it right- technically, culturally, and contextually.  Then help the company use success in that one area or workload to change other area, processes, and workloads.  So yes it is transforming companies with digital technologies but it’s not about a “DT” button you can press and voila! -things work. 

Marketing Darwinism: You work with some amazingly successful, big names.  Does that create pressure on the company?

Dharmesh: We work with the largest of the large tech companies and with startups.  We are drawn to challenges and patterns where we can honestly add value.  We also work with a variety of organizations in what are called “traditional” industries.  That’s where most of the work done is and where most people in the country are employed.  We learn amazing things from manufacturing and services companies daily and can then apply these learnings to other companies looking to evolve and hone their offerings.  Yes, the “ways” of large companies can create pressure but we thrive in the cauldron and love every minute of it.

Marketing Darwinism: What are your big bets for 2019 and 2020? What are you most excited about?

Dharmesh: We are incredibly excited about helping companies find new life with the proper use of the amazing Business Applications and Analytics packages  available in the market today.   It was unheard of, even a few years ago, to be able to run complex infrastructure with complex tasks in an agile manner without pitting IT and Business against each other.  We thrive on building internal bridges in our customers and watching them do amazing things.  So, I can say that our big bet for the next 18 month is Business Apps.and Analytics  We also have invested heavily in our “Managed Services” business which is growing rapidly and allowing us to really feel “as one” with many of our customers.

Marketing Darwinism:   We’d be remiss if we didn’t talk about Marketing.  Two prongs here- what are you doing to help your customers market and how are you using marketing to gain traction?

Dharmesh: Great questions.  We continue to do a lot of work in what we call TMAAS- Technical Marketing-As-A-Service.  We believe that Enterprise technology has to be talked about in a narrative manner that connects value to all aspects of purchase, implementation and tweaking.  We also believe that Brand building and Sales Enablement are connected and we offer that perspective to our customers.

In terms of our own efforts, we gain a lot from events, 1: few executive conclaves, and work of mouth marketing.  Though we are small, we spend considerably in those areas and have been lucky to realize success there.  Increasingly, we co-market with our customers and this also has yielded fruit.

Marketing Darwinism:   Any parting thoughts?

Dharmesh: Thanks so much Paul. We want believe that global delivery models aligned to real value conversations are the keys to success.  We hope to double our size in the next 18 months and are very thankful to our customers, partners, and well-wishers for all their support.

March 29, 2019by 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
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
Data Analytics, Transformation

Digital Transformation as an Expression of Business

In much of industry, the idea of “Digital Transformation” has taken root. At the core of this process is the need to replace antiquated and “slow” processes, products, and service offerings with agile, automated, and “smart” processes, products, and service offerings. In addition, digital transformation is about the inclusion of all potentially interested parties (employees, partners, customers, influencers) in the creation and execution of new lines of business and innovation.

While the concept of Digital Transformation has been around in the entire Internet Age, necessary elements have indeed been missing. First, not always were the underlying technologies ready for “prime-time.” What works in manicured and controlled environments doesn’t always work at scale or in fast-moving, instant-decision environments. Second, the culture of transformation has not always been present with many forces internally and externally being focused on the power of the status quo. Third, Digital Transformation requires the foregrounding of certain parts of the organization at the perceived expense of others parts. With these constraints, the prevailing scenario for transformation has been characterized by the gap between intention and execution.

Of the organizational barriers that impede the progress for Digital Transformation, the schism between IT and Business is perhaps the most profound. Business users in organizations are governed by entirely different imperatives than IT teams are. While business changes, roles and cultures do not always keep up with the dynamism of business models and the directives that come out of the C-suite.

Business users are defined by the “Power of NOW!” while IT is chartered with issues of security, governance, compliance (and at times control) that if applied in the canonical methodology, are antagonistic to the time-based agility that has come to define modern business.

This happens even when IT teams and Business teams are friendly and believe in the same overall set of goals. This is the result of technology configurations that were not flexible or adaptive, two defining characteristics of true Digital Transformation.

When IT and Business are in Harmony, agility is possible in a way that does not run afoul of the core mandates of IT. When IT and Business are in structural harmony, all of the manic energies of the organization can be trained on the same end goal.

Running IT like a Business and running Business in an IT-native world are keys to Digital Transformation. At stake here is the ability of organizations to navigate the shoals of modernity and complexity, in which every expanding pools of data and ever-growing avenues of expansion characterize business.

As such, Digital Transformation is the ultimate expression of IT-Business Harmony and IT-Business Harmony is the starting point of real Digital Transformation.

Guest post by:
Romi Mahajan, KKM Group
Srini Venugopal, Epicor Software

May 11, 2017by 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
Business Intelligence, Data Analytics, Data Mining, Listening, Reputation Monitoring, Social Business Intelligence, Social Customer Service, Social Media

Social Listening: Harness Marketing Insights from Consumer Conversations

shutterstock_234298024

This week I moderated another Social Media Today webinar as part of their Best Thinker webinar series, this time on the topic of Social Listening: Harness Marketing Insights from Consumer Conversations. This webinar featured Kevin Hack (@kevinhack) head of Social Intelligence in Global Digital Marketing Advancement at The Hershey Company, Kendra Simpson (@Kfoley) Director of Communications at Kohler Company, Drew Neisser (@DrewNeisser) founder and CEO of Renegade and Will McInnes (@willmcinnes) Integrated Marketing Analyst at Union+Webster. This webinar was sponsored by Brandwatch. We discussed tips and tricks for finding and utilizing Social Listening in your organization!

Here are three key takeaways from the webinar:

  1. Customer Centric? – How can you declare that you are customer centric if you don’t do Social Listening!
  2. ROI of Social Listening – what’s the ROI of not listening to your customers – most likely it more than the cost of Social Listening
  3. Social to predict what’s next – more and more social is being used to find opportunities in product development or innovation

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 Storytelling Gone Wild: The Key to Creating Viral Content be sure to sign up for it or view the schedule of other upcoming webinars here.

February 10, 2016by Paul Dunay
Data, Data Analytics, Data Mining

Interview with Gregg Thaler from RingLead

Gregg Thaler

Here is a recent interview with my new friend, Gregg Thaler, is a self-professed data quality junkie and the Chief Revenue Officer of RingLead. We discussed some best practices in data. I hope you enjoy!

PD:     How often is poor data the downfall of a marketing campaign?

GT:     Well, if I said every time, that would be a bit of hyperbole, but only a bit. Typically what I find with lists – especially trade show lists – is that they are the Typhoid Mary of duplicate creation in your database. Very often if you think about trade shows, who attends your booth? Many times it’s your customers or existing prospects. And booth staff will scan them indiscriminately. If you import that list without taking preventative measures, then it creates a duplicates horror show.

So, there’s another category of bad lists and those are the lists that are purchased from vendors. And there’s a very fundamental reason why lists purchased from data vendors have data quality challenges. The challenge with contact data is that it ages like fish and not like fine wine. It gets worse as it gets older, not better. Data is foundational. CRM and marketing automation are merely vessels, it is the data they contain that is the true treasure. It’s the single most critical element when it comes to determining revenue success of failure. Everything else you do further down the order of operations, its’ outcome depends completely on the input. What do you get from an automated process when you put garbage in? Garbage out.

 

PD:     What would you say is one of the biggest mistakes you see B2B marketers making when it comes to data?

GT:     Well, the mistake that I’m going to describe isn’t really limited to marketers. If you want to really truly recognize the strategic benefits of having optimized data, you have to have a mindset to prevent errors at the source. There’s a simple reason for that. Generally speaking, whatever the cost is in the enterprise to get the data right at the point of creation it’s going to cost you ten times that later to fix it. But then, of course, if you do nothing, the damage caused by inferior data could be much worse, 100x worse is possible.

So often marketers come to us, and their hair is on fire they’ve got to dedupe their database right now. Yes, they’re right. You do have to remediate the situation since almost every single contact database is riddled with duplicate and non-standard data. Often, however, I hear brilliant marketers say something incredibly dumb, they’ll say “…we’ll worry about the prevention later.” Are you kidding me?

 

PD:     Who ultimately owns the data? It is really sales who owns it, or is it really marketing?

GT:     That’s a terrific question. Where should data governance reside? Who is the data steward? Traditionally it has been IT. Increasingly we are seeing the data steward role reside in marketing and sales which is where I rightly believe it should belong. Now, what we see in the market, most often the actual people who perform these data janitor-like tasks, are usually in marketing operations, followed very closely by their colleagues in sales ops. Really the best practice is, I believe that organizations should have a data quality center of excellence typically reporting into sales and marketing operations. Even if the COE is one person.

 

PD:     Let’s talk about the best way to boost productivity in marketing.

GT:     This has, of late, become a favorite topic of mine. I think it’s something that’s very under-focused on as it relates to peak performance not just for marketers, but throughout the organization. What I’m talking about is first the batch normalization of an org’s data and then the automated enforcement of data standards with technology.

I spoke to two very well-known technology companies. I asked them “how many technologies do you have in your marketing stack?” One responded 35 and another said 22. When you think about the performance efficiencies of all of those applications operating on, what for most people, is a completely non-standard set of data. That contributes to very poor application performance which would then translate into poor performance across the entire marketing stack. It’s a silent killer of revenue and application performance. People probably aren’t aware of how well those applications could perform on a standardized data set. They’ve never seen one. In the benchmarking we’ve done, we’ve seen eye-popping performance gains of up to 600% in duplicate detection in a standardized vs. non-standardized data set. Compound that kind of application performance improvement across the 35 apps that modify that data set and the gains in application performance can be off the charts.

I am completely convinced that data standardization is the single most impactful action, a unique foundation-level enabler that marketers and sales professionals can take to optimize their data for revenue performance and their applications for speed, accuracy and efficient operation.

October 22, 2015by 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
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
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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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