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This is a guest post by Lauren Jung, Co-Founder of dunnhumby Ventures portfolio company TheShelf.com

 

At one time or another, we’ve all been convinced to buy products based on biased claims made by brands, only to discover that the product wasn’t as great as its shiny marketing implied. This has caused consumers to become increasingly wary of any branded marketing, leading them to seek out validation from their own trusted sources before making a purchase decision. 

This concept isn’t new and there are tons of of statistics out there to prove that brands need to incorporate more organic marketing tactics into their strategy. According to Bazaar Voice, 84% of shoppers now look to reviews prior to making a purchase decision. What’s more, sharing your content through influencers in your industry is found to increase conversion by at least a 3x-10x higher rate, says Content Marketing Institute.

With this much emphasis placed on the recommendations of an unbiased third-party, word-of-mouth is no longer optional. It’s a requirement in modern marketing. Everyday people and even customers have become the driving force behind sales, leading to a paradigm shift that is happening within the marketing world. 

This Shift is a Messy One

This shift in marketing has turned the well-established Path-To-Purchase model on its head, giving rise to a much more dynamic Path, one that is different for each industry. Google has analyzed millions of consumer interactions via Google Analytics and using this data, they’ve designed a visualization of the effects that variables like company size, industry, and location have on a brand’s Path-To-Purchase. The new Path-To-Purchase has become an ever-changing moving target, requiring marketers to constantly be on their feet, ready to adapt at a moment’s notice.

This shift in influence is further complicated by new social networks being thrust into the equation each year. This year it was Snapchat and Ello.  Last year, Vine. Savvy brands recognize that this new frontier in marketing requires a creative cocktail of techniques in order to effectively target their unique audience. There’s no “one size fits all” solution anymore: brands that are more visual in nature (e.g. fashion, beauty, decor, travel) lean heavily on visual networks like Pinterest, Instagram, YouTube, and Vine, while B2B companies that produce tons of long-form content are all over LinkedIn, Twitter and Google+. And then there are brands that are trying to appeal to millennials, so they’re allocating huge budgets towards newer platforms, like SnapChat and Instagram.

Targeting and relevance are another huge challenge. It’s not enough to just find someone who’s popular; in fact, it’s becoming clear as this form of marketing evolves that popularity has very little to do with influence. Brands are starting to explore relationships with mid-range influencers who have deep engagement with their audiences and are even outperforming larger thought leaders. "The whole idea is based on audiences trusting their peers more than brands," says Tom Buontempo, President, Attention, KBS Content Labs. He adds, "Audiences are more sophisticated and they can sniff out when a partnership doesn't feel authentic." According to the Technorati Digital Influence Report, 54% of customers believe the smaller the community, the larger the influence. Brands are tasked with finding very specific influencers who have the ear of their exact target demographic.

And if that isn’t enough, the final aspect that brands need to consider is also the trickiest. Unlike buying clicks via Adwords or Sponsored Tweets (where a brand is guided through a carefully designed setup process, followed by the immediate gratification of their pre-purchased clicks) the world of word-of-mouth and influencer marketing is like the Wild West of marketing. Aside from some mild FTC restrictions, it’s largely an unmoderated and an “anything-goes” sort of setup. No one is in charge. Millions upon millions of bloggers and social influencers are deciding willy-nilly what the going-rate is for their endorsement. Influence ain’t cheap! Additionally, results are not guaranteed. Brands are essentially placing bets on who is going to pay off for them. And these bets require a hefty amount of due diligence due to the fact that many social influencers resort to shady tactics like buying followers and inflating their vanity metrics in order to boost their appeal. 

It’s Worth Getting Your Hands Dirty

Despite all of the annoyances that come with this new territory, brands are going all-in because the ROI potential is quickly surpassing that of more traditional forms of marketing, with many brands seeing unprecedented returns when marketing through their more vocal and influential customers. 

On average, marketers who implemented an Influencer Marketing program in 2014 received $6.85 in earned media value for every $1.00 of paid media! Three industries performed above the $6.85 average, consumer packaged goods and food generated $11.33 per $1.00 spent, and retail and apparel generated $10.48. (More stats available in our Influencer Marketing Infographic here.)

So despite the mayhem that one can expect when jumping into the influencer marketing scene, brands don’t have much of a choice. Those who decide to sit out are going to get left behind. According to Social Media Today, 74% of global marketers say they will use ‘influence marketing’ as part of their marketing strategy in the next 12 months.  What’s more, Adweek points out that nearly 60% of marketers plan to boost influencer marketing budgets.

Can one automate authenticity?

With every new addition to the marketer’s toolkit, comes a deluge of companies trying to provide an automated solution. When banner ads were all the rage, a variety of sites like Perfect Audience, Adroll, and ReTargeter came along to aggregate all of these efforts under one roof. As content marketing skyrocketed in popularity, thousands of companies like Hubspot, Contently, and Outbrain each took a unique stab at streamlining the tedious process of content creation and distribution. For social media, there’s Buffer, Hootsuite, Sprout Social, and thousands of other options out there that eliminate the legwork involved in constantly being present on the various social networks. 

Influencer marketing is a very different beast, compared to earlier, more established marketing channels, in one key way. It relies on a very unreliable variable: the free-will of unbiased people, thus making automation a very difficult thing to achieve. Automation breeds insincerity and that is the opposite of everything that influencer marketing stands for. Customers crave unbiased, organic recommendations from the people they trust. That’s the bottom line.

Of course that doesn’t stop the thousands of businesses out there that are hard at work building products that they claim will fix this space through automation. Since this marketing channel is still relatively young, brands will continue to get suckered into buying these various solutions, in hopes that it will be that magic tool that will make their job a little easier.

There’s no denying the need for that elusive, magical solution. Influencer marketing is full of potential but it’s hard to tap into for the same reasons that make it so great. It’s wild and organic and automation would only defeat its purpose.

So could it be that these automation services have it wrong? Could it be that the solution to this problem isn’t a point-and-click wizzy-wig product, but something a little less obvious? Something more fundamental?

The Need for a Data-Driven Solution

Since the birth of the internet and social networks, people have become connected in a completely different way. Geographical boundaries have become irrelevant. People from anywhere in the world are able to connect with one another based on literally anything - celebrities that they follow, hobbies they enjoy, imagery they find inspiring, political views they subscribe to, health problems they want to research, songs they listen to, brands they love, and products they’re buying. People everywhere are connected by their interests that are manifested through the content they create and share.

These connections are becoming more and denser as time goes on due to the sheer volume at which new content and connections are being generated.

  • 69,120 hours of video are uploaded to YouTube every day
  • 985,648,320 pieces of content are shared on Facebook everyday 
  • 144,000,000 tweets are posted per day
  • 5,184,000 Instagram photos are shared per day 

And the list goes on. 

This content, and the various interests that this content represents, forges these connections between people.

To put it another way, people are increasingly inter-connected to one another by their interests through the “content”:

  • They endorse these interests
  • They engage with others about these interests
  • And they are producing a constant stream of content that highlights these interests…

In essence, they’re forming an ever growing web of interest...or as we like to call it, a global interest graph. 

When you think about this global interest graph from a strictly ecommerce perspective, hidden within this deluge of content, opinions, connections, and endorsements are nuggets of marketing gold. Brands are connected to influencers, who are connected to consumers, all of whom are connected even further via individual products and even purchases. Imagine the power a brand could attain if this graph was queryable. All of this raw noisy data would suddenly be actionable. What customers have influence over my specific demographic? Who is influencing my currently untapped markets? What pricing structure will sell more of my products? When is the right time to run promotions? What trends are getting ready to erupt?

Additionally, this global interest graph would have the power to supercharge any number of existing marketing initiatives through the use of big data, allowing brands a level of targeting that would never before have been possible: loyalty programs, ad networks, influencer marketing, trend prediction, drip campaigns, social listening, sentiment analysis, recommendation engines, and much more. All of these solutions exist separately today, yet they are very much interconnected via the global interest graph.

Conclusion

Brands need to make sure that they are a part of this wave of influence. Authenticity is everything…it’s a requirement for brands in today’s market. In order to achieve good results, brands need to focus on what matters most: marketing via the influencers who are in the best position to sell their products. This requires a data-driven approach to locate these very specific people within the sea of millions of other influencers fighting for attention, as well as constructing campaigns that will speak to their unique audience. As I mentioned before, there’s no one-size-fits all here. This industry is exploding with potential and for the time being, anyone who tries their hand at it, should be prepared to roll up their sleeves a bit. Because it’s still a little messy.

With all of the attention that this space is getting right now, a novel solution is inevitable. But it will most definitely look different from the obvious solutions available today that rely on simplification via automation. Rather than focusing on how to automate authenticity, a notion that is completely oxymoronic, the end solution is going to be a data-driven one, that provides access to the immense amount of data currently hidden within this global interest graph. When this feat has been achieved, the face of advertising could be fundamentally changed forever.

Bio

Lauren is the co-founder of TheShelf.com, an influencer marketing platform that enables brands and pr agencies to connect with the most relevant influencers, run campaigns, analyze results, and monitor competition. They currently serve businesses in the fashion, beauty, lifestyle, travel, food, and family spaces. Twitter : @thelaurenjung

This is a guest post by Lauren Jung, Co-Founder of dunnhumby Ventures portfolio company TheShelf.com

 

At one time or another, we’ve all been convinced to buy products based on biased claims made by brands, only to discover that the product wasn’t as great as its shiny marketing implied. This has caused consumers to become increasingly wary of any branded marketing, leading them to seek out validation from their own trusted sources before making a purchase decision. 

This concept isn’t new and there are tons of of statistics out there to prove that brands need to incorporate more organic marketing tactics into their strategy. According to Bazaar Voice, 84% of shoppers now look to reviews prior to making a purchase decision. What’s more, sharing your content through influencers in your industry is found to increase conversion by at least a 3x-10x higher rate, says Content Marketing Institute.

With this much emphasis placed on the recommendations of an unbiased third-party, word-of-mouth is no longer optional. It’s a requirement in modern marketing. Everyday people and even customers have become the driving force behind sales, leading to a paradigm shift that is happening within the marketing world. 

This Shift is a Messy One

This shift in marketing has turned the well-established Path-To-Purchase model on its head, giving rise to a much more dynamic Path, one that is different for each industry. Google has analyzed millions of consumer interactions via Google Analytics and using this data, they’ve designed a visualization of the effects that variables like company size, industry, and location have on a brand’s Path-To-Purchase. The new Path-To-Purchase has become an ever-changing moving target, requiring marketers to constantly be on their feet, ready to adapt at a moment’s notice.

This shift in influence is further complicated by new social networks being thrust into the equation each year. This year it was Snapchat and Ello.  Last year, Vine. Savvy brands recognize that this new frontier in marketing requires a creative cocktail of techniques in order to effectively target their unique audience. There’s no “one size fits all” solution anymore: brands that are more visual in nature (e.g. fashion, beauty, decor, travel) lean heavily on visual networks like Pinterest, Instagram, YouTube, and Vine, while B2B companies that produce tons of long-form content are all over LinkedIn, Twitter and Google+. And then there are brands that are trying to appeal to millennials, so they’re allocating huge budgets towards newer platforms, like SnapChat and Instagram.

Targeting and relevance are another huge challenge. It’s not enough to just find someone who’s popular; in fact, it’s becoming clear as this form of marketing evolves that popularity has very little to do with influence. Brands are starting to explore relationships with mid-range influencers who have deep engagement with their audiences and are even outperforming larger thought leaders. "The whole idea is based on audiences trusting their peers more than brands," says Tom Buontempo, President, Attention, KBS Content Labs. He adds, "Audiences are more sophisticated and they can sniff out when a partnership doesn't feel authentic." According to the Technorati Digital Influence Report, 54% of customers believe the smaller the community, the larger the influence. Brands are tasked with finding very specific influencers who have the ear of their exact target demographic.

And if that isn’t enough, the final aspect that brands need to consider is also the trickiest. Unlike buying clicks via Adwords or Sponsored Tweets (where a brand is guided through a carefully designed setup process, followed by the immediate gratification of their pre-purchased clicks) the world of word-of-mouth and influencer marketing is like the Wild West of marketing. Aside from some mild FTC restrictions, it’s largely an unmoderated and an “anything-goes” sort of setup. No one is in charge. Millions upon millions of bloggers and social influencers are deciding willy-nilly what the going-rate is for their endorsement. Influence ain’t cheap! Additionally, results are not guaranteed. Brands are essentially placing bets on who is going to pay off for them. And these bets require a hefty amount of due diligence due to the fact that many social influencers resort to shady tactics like buying followers and inflating their vanity metrics in order to boost their appeal. 

It’s Worth Getting Your Hands Dirty

Despite all of the annoyances that come with this new territory, brands are going all-in because the ROI potential is quickly surpassing that of more traditional forms of marketing, with many brands seeing unprecedented returns when marketing through their more vocal and influential customers. 

On average, marketers who implemented an Influencer Marketing program in 2014 received $6.85 in earned media value for every $1.00 of paid media! Three industries performed above the $6.85 average, consumer packaged goods and food generated $11.33 per $1.00 spent, and retail and apparel generated $10.48. (More stats available in our Influencer Marketing Infographic here.)

So despite the mayhem that one can expect when jumping into the influencer marketing scene, brands don’t have much of a choice. Those who decide to sit out are going to get left behind. According to Social Media Today, 74% of global marketers say they will use ‘influence marketing’ as part of their marketing strategy in the next 12 months.  What’s more, Adweek points out that nearly 60% of marketers plan to boost influencer marketing budgets.

Can one automate authenticity?

With every new addition to the marketer’s toolkit, comes a deluge of companies trying to provide an automated solution. When banner ads were all the rage, a variety of sites like Perfect Audience, Adroll, and ReTargeter came along to aggregate all of these efforts under one roof. As content marketing skyrocketed in popularity, thousands of companies like Hubspot, Contently, and Outbrain each took a unique stab at streamlining the tedious process of content creation and distribution. For social media, there’s Buffer, Hootsuite, Sprout Social, and thousands of other options out there that eliminate the legwork involved in constantly being present on the various social networks. 

Influencer marketing is a very different beast, compared to earlier, more established marketing channels, in one key way. It relies on a very unreliable variable: the free-will of unbiased people, thus making automation a very difficult thing to achieve. Automation breeds insincerity and that is the opposite of everything that influencer marketing stands for. Customers crave unbiased, organic recommendations from the people they trust. That’s the bottom line.

Of course that doesn’t stop the thousands of businesses out there that are hard at work building products that they claim will fix this space through automation. Since this marketing channel is still relatively young, brands will continue to get suckered into buying these various solutions, in hopes that it will be that magic tool that will make their job a little easier.

There’s no denying the need for that elusive, magical solution. Influencer marketing is full of potential but it’s hard to tap into for the same reasons that make it so great. It’s wild and organic and automation would only defeat its purpose.

So could it be that these automation services have it wrong? Could it be that the solution to this problem isn’t a point-and-click wizzy-wig product, but something a little less obvious? Something more fundamental?

The Need for a Data-Driven Solution

Since the birth of the internet and social networks, people have become connected in a completely different way. Geographical boundaries have become irrelevant. People from anywhere in the world are able to connect with one another based on literally anything - celebrities that they follow, hobbies they enjoy, imagery they find inspiring, political views they subscribe to, health problems they want to research, songs they listen to, brands they love, and products they’re buying. People everywhere are connected by their interests that are manifested through the content they create and share.

These connections are becoming more and denser as time goes on due to the sheer volume at which new content and connections are being generated.

  • 69,120 hours of video are uploaded to YouTube every day
  • 985,648,320 pieces of content are shared on Facebook everyday 
  • 144,000,000 tweets are posted per day
  • 5,184,000 Instagram photos are shared per day 

And the list goes on. 

This content, and the various interests that this content represents, forges these connections between people.

To put it another way, people are increasingly inter-connected to one another by their interests through the “content”:

  • They endorse these interests
  • They engage with others about these interests
  • And they are producing a constant stream of content that highlights these interests…

In essence, they’re forming an ever growing web of interest...or as we like to call it, a global interest graph. 

When you think about this global interest graph from a strictly ecommerce perspective, hidden within this deluge of content, opinions, connections, and endorsements are nuggets of marketing gold. Brands are connected to influencers, who are connected to consumers, all of whom are connected even further via individual products and even purchases. Imagine the power a brand could attain if this graph was queryable. All of this raw noisy data would suddenly be actionable. What customers have influence over my specific demographic? Who is influencing my currently untapped markets? What pricing structure will sell more of my products? When is the right time to run promotions? What trends are getting ready to erupt?

Additionally, this global interest graph would have the power to supercharge any number of existing marketing initiatives through the use of big data, allowing brands a level of targeting that would never before have been possible: loyalty programs, ad networks, influencer marketing, trend prediction, drip campaigns, social listening, sentiment analysis, recommendation engines, and much more. All of these solutions exist separately today, yet they are very much interconnected via the global interest graph.

Conclusion

Brands need to make sure that they are a part of this wave of influence. Authenticity is everything…it’s a requirement for brands in today’s market. In order to achieve good results, brands need to focus on what matters most: marketing via the influencers who are in the best position to sell their products. This requires a data-driven approach to locate these very specific people within the sea of millions of other influencers fighting for attention, as well as constructing campaigns that will speak to their unique audience. As I mentioned before, there’s no one-size-fits all here. This industry is exploding with potential and for the time being, anyone who tries their hand at it, should be prepared to roll up their sleeves a bit. Because it’s still a little messy.

With all of the attention that this space is getting right now, a novel solution is inevitable. But it will most definitely look different from the obvious solutions available today that rely on simplification via automation. Rather than focusing on how to automate authenticity, a notion that is completely oxymoronic, the end solution is going to be a data-driven one, that provides access to the immense amount of data currently hidden within this global interest graph. When this feat has been achieved, the face of advertising could be fundamentally changed forever.

Bio

Lauren is the co-founder of TheShelf.com, an influencer marketing platform that enables brands and pr agencies to connect with the most relevant influencers, run campaigns, analyze results, and monitor competition. They currently serve businesses in the fashion, beauty, lifestyle, travel, food, and family spaces. Twitter : @thelaurenjung

06 May 2015

There is something amusing and yet equally alarming about Pret a Manger going public with its policy of bestowing random acts of kindness on unsuspecting customers.

A free cappuccino for the man with a nice tie, or a croissant for the couple who speak the barista’s native Portuguese.

The amusing part is not the quirkiness of the idea, but the assumption that it will be universally well received. Perhaps we might even start going there on the off chance of a freebie?

I’m a very loyal Pret customer. I would almost go as far as saying I have lunch from Pret four times a week and munch on popcorn and chocolate covered rice cakes as snack staples. Not once in the last two years have I been given a free anything. So, with this fact in the forefront of my mind, has Pret got it right or really very wrong?

It depends on what Pret wants to achieve. It’s unlikely the company set out to provide fair recognition of customers’ loyalty, judging by the examples Pret’s CEO Clive Schee gave of the idea in action, which included “I fancy that girl or that boy”.

Good business sense

However, creating moments of unexpected happiness for both customers and for employees is good business sense.

It gets our attention, makes us feel special and punctuates our day with something that is enjoyable and memorable. You’ll probably talk about it, tell someone and share the great news about this act of appreciation and attention.

This is the stuff of brand building, culture creation and a marketing man or woman’s dream. Twitter will light up with the tweets and customers will come to check you out.

The problem is that placing customer relationship management in the hands of employees exercising their personal judgement about who deserves special treatment is simply not fair. All sorts of biases kick in and many highly loyal customers will never feel recognised.

It will be interesting to see whether these customers will be less inclined to shop at Pret since this tactic has become public, as well as how it might affect consumer behaviour in-store.

Could there be overt flirtation and self-promotion on entry, followed by indignation felt and frustration muttered on exit. Employees might find this tricky to manage.

There are businesses that have managed to create surprise and delight CRM strategies that apply internal rules and controls, making these fair yet flexible within boundaries.

The US bakery-café chain Panera Bread, for instance, has created MyPanera, rewarding customers with relevant surprises from complimentary bakery items and recipe books to invitations to events and tastings.

It would be a shame if Pret’s initiative sparked a wave of approaches that are headline grabbing, but really make just a few people feel special and everyone else a tinge disappointed every time they buy.

There’s a place for random acts of kindness and giving employees some power to exercise their discretion, but this doesn’t trump fair rewards based on real personal insight.

This article originally appeared on Retail Week: http://www.retail-week.com/comment/comment-prets-loyalty-scheme-does-not-trump-fair-rewards-based-on-insight/5074355.article?blocktitle=Latest-news-&-analysis&contentID=15015


There is something amusing and yet equally alarming about Pret a Manger going public with its policy of bestowing random acts of kindness on unsuspecting customers.

A free cappuccino for the man with a nice tie, or a croissant for the couple who speak the barista’s native Portuguese.

The amusing part is not the quirkiness of the idea, but the assumption that it will be universally well received. Perhaps we might even start going there on the off chance of a freebie?

I’m a very loyal Pret customer. I would almost go as far as saying I have lunch from Pret four times a week and munch on popcorn and chocolate covered rice cakes as snack staples. Not once in the last two years have I been given a free anything. So, with this fact in the forefront of my mind, has Pret got it right or really very wrong?

It depends on what Pret wants to achieve. It’s unlikely the company set out to provide fair recognition of customers’ loyalty, judging by the examples Pret’s CEO Clive Schee gave of the idea in action, which included “I fancy that girl or that boy”.

Good business sense

However, creating moments of unexpected happiness for both customers and for employees is good business sense.

It gets our attention, makes us feel special and punctuates our day with something that is enjoyable and memorable. You’ll probably talk about it, tell someone and share the great news about this act of appreciation and attention.

This is the stuff of brand building, culture creation and a marketing man or woman’s dream. Twitter will light up with the tweets and customers will come to check you out.

The problem is that placing customer relationship management in the hands of employees exercising their personal judgement about who deserves special treatment is simply not fair. All sorts of biases kick in and many highly loyal customers will never feel recognised.

It will be interesting to see whether these customers will be less inclined to shop at Pret since this tactic has become public, as well as how it might affect consumer behaviour in-store.

Could there be overt flirtation and self-promotion on entry, followed by indignation felt and frustration muttered on exit. Employees might find this tricky to manage.

There are businesses that have managed to create surprise and delight CRM strategies that apply internal rules and controls, making these fair yet flexible within boundaries.

The US bakery-café chain Panera Bread, for instance, has created MyPanera, rewarding customers with relevant surprises from complimentary bakery items and recipe books to invitations to events and tastings.

It would be a shame if Pret’s initiative sparked a wave of approaches that are headline grabbing, but really make just a few people feel special and everyone else a tinge disappointed every time they buy.

There’s a place for random acts of kindness and giving employees some power to exercise their discretion, but this doesn’t trump fair rewards based on real personal insight.

This article originally appeared on Retail Week: http://www.retail-week.com/comment/comment-prets-loyalty-scheme-does-not-trump-fair-rewards-based-on-insight/5074355.article?blocktitle=Latest-news-&-analysis&contentID=15015

27 Apr 2015

Published in AdExchanger

The big data revolution helped to create a new job title: the data scientist. The title, which Harvard Business Review called the “sexiest job of the 21st century,” – became so popular that the ambiguity of the description grew to include everything from statistical analysis to database management – two very distinct and different roles.

It has already been suggested that the title be killed off for this reason. Instead, I believe what the marketing industry really needs is the a different title: “insights artist.”

The ability to amass large amounts of data from various sources is important – and best left to data management specialists. The ability to organize data and use it for targeting and measurement purposes is equally important – and best left to statistical analysts. But making sense of the world – in terms of what consumers are doing, what they want and how they want it, in a way that can then turn all of that into a marketing strategy – requires a special set of skills that isn’t easy to find.

More Art Than Science

Analyzing data is a science. I learned all about it in graduate school, and I can still do linear regression by hand with paper and pencil if needed. What they don’t teach you in school is how to apply all of the critical thinking and statistical analysis to the data to make it come alive. That involves turning data into customer insights, from which a strategy can be built. That requires more art than science, and lots of experience.

A “data artist” can turn data and metrics into a visually appealing graph or chart that makes the data easier to interpret. Thus, infographics have become extremely popular for conveying complex ideas in an easier-to-understand medium. An insights artist combines the skills of an analyst and a data artist, with the strategy of a marketer to go a few steps further and turn it into a brilliant business plan.

Insights artists must understand the business needs and what exactly needs to be solved. They need to see the whole picture from the the data, business and customer perspectives, from the business application perspective and – most importantly – from the customer perspective. This is where all good data analysis begins. Just having massive amounts of data is not enough; it doesn’t automatically turn into insights that can be used. Once the business problems are understood, there is always a matter of choosing the right tools or statistical methods, etc. When the analysis is complete and there are compelling results to share, they have to be boiled down into a few meaningful charts and graphs for the rest of the world to understand.

Metrics: A Key Piece Of The Puzzle

After the logical thinking and investigative work of the analyst is applied to the data, and the informative yet easy-to-understand graphic development of the data artist is applied to the results, a story begins to emerge. This is where an insights artist separates from the rest. Too often, an analyst will do brilliant work only to fall flat when it's presented. While it may be on point and statistically sound, it doesn’t resonate with the audience, which is trying to understand how the data is supposed to guide decision-making.

Knowing which metrics to share is a critical piece of the puzzle. Analysts always want to show how much work they did, because it is a lot of work. This often leads to an endless PowerPoint presentation that has too much “What?” and not enough “So what?” or “Now what?”

Do you need to present ROI as raw dollar uplift, incremental net sales without margin or incremental units sold? These are just different mathematical formulas. What comes after the assimilation of results is more crucial to developing a successful marketing plan. Why was the ROI so low or so high? Did one creative asset work better than another? Most importantly, an insights artist should answer the question: What should we do differently next time to make the campaign even more successful?

How the metrics are presented is part of the art that is applied after the science. An analyst, for example, would say that in the last six months, the number of lapsed buyers of a brand totaled 4.4 million customers. A data artist would show a map that equates that number to the population of Kentucky. An insights artist shows the same information but also decomposes the reasons behind the lapsed customers, along with insight into: Were they brand-loyal or brand-switchers? Which brand did they migrate to, or are they out of the market altogether? Which segments can potentially be won back, and which tactics have previously worked in the past to bring customers back?

Searching For Insights Artists

Of course, finding someone with all of these traits is not easy, especially when the single most important factor to being an insights artist is experience.

In a perfect world, every organization searching for a data scientist would be hiring a former analyst who has spent the last 10 years as a marketing manager. But those people aren’t easy to find. An alternative would be to stop looking for one Renaissance man or woman to do it all – and instead solve this skills/experience combination problem by assembling the right mix of people. Often, the best solutions are derived from collaboration.

When an analyst, data artist, and marketing manager can all come together and understand the value each brings to the equation, success is more easily achieved.

So I propose we kill the data scientist title in favor of the insights artist. In reality, this is most likely a team of traditional roles that organizations have been hiring for years: analysts and marketing managers. The key is to stop isolating them in departmental silos and bring them together, so that each understands the problem, the potential solutions, and the best way to convert massive amounts of data into actionable insights.

 

Published in AdExchanger

The big data revolution helped to create a new job title: the data scientist. The title, which Harvard Business Review called the “sexiest job of the 21st century,” – became so popular that the ambiguity of the description grew to include everything from statistical analysis to database management – two very distinct and different roles.

It has already been suggested that the title be killed off for this reason. Instead, I believe what the marketing industry really needs is the a different title: “insights artist.”

The ability to amass large amounts of data from various sources is important – and best left to data management specialists. The ability to organize data and use it for targeting and measurement purposes is equally important – and best left to statistical analysts. But making sense of the world – in terms of what consumers are doing, what they want and how they want it, in a way that can then turn all of that into a marketing strategy – requires a special set of skills that isn’t easy to find.

More Art Than Science

Analyzing data is a science. I learned all about it in graduate school, and I can still do linear regression by hand with paper and pencil if needed. What they don’t teach you in school is how to apply all of the critical thinking and statistical analysis to the data to make it come alive. That involves turning data into customer insights, from which a strategy can be built. That requires more art than science, and lots of experience.

A “data artist” can turn data and metrics into a visually appealing graph or chart that makes the data easier to interpret. Thus, infographics have become extremely popular for conveying complex ideas in an easier-to-understand medium. An insights artist combines the skills of an analyst and a data artist, with the strategy of a marketer to go a few steps further and turn it into a brilliant business plan.

Insights artists must understand the business needs and what exactly needs to be solved. They need to see the whole picture from the the data, business and customer perspectives, from the business application perspective and – most importantly – from the customer perspective. This is where all good data analysis begins. Just having massive amounts of data is not enough; it doesn’t automatically turn into insights that can be used. Once the business problems are understood, there is always a matter of choosing the right tools or statistical methods, etc. When the analysis is complete and there are compelling results to share, they have to be boiled down into a few meaningful charts and graphs for the rest of the world to understand.

Metrics: A Key Piece Of The Puzzle

After the logical thinking and investigative work of the analyst is applied to the data, and the informative yet easy-to-understand graphic development of the data artist is applied to the results, a story begins to emerge. This is where an insights artist separates from the rest. Too often, an analyst will do brilliant work only to fall flat when it's presented. While it may be on point and statistically sound, it doesn’t resonate with the audience, which is trying to understand how the data is supposed to guide decision-making.

Knowing which metrics to share is a critical piece of the puzzle. Analysts always want to show how much work they did, because it is a lot of work. This often leads to an endless PowerPoint presentation that has too much “What?” and not enough “So what?” or “Now what?”

Do you need to present ROI as raw dollar uplift, incremental net sales without margin or incremental units sold? These are just different mathematical formulas. What comes after the assimilation of results is more crucial to developing a successful marketing plan. Why was the ROI so low or so high? Did one creative asset work better than another? Most importantly, an insights artist should answer the question: What should we do differently next time to make the campaign even more successful?

How the metrics are presented is part of the art that is applied after the science. An analyst, for example, would say that in the last six months, the number of lapsed buyers of a brand totaled 4.4 million customers. A data artist would show a map that equates that number to the population of Kentucky. An insights artist shows the same information but also decomposes the reasons behind the lapsed customers, along with insight into: Were they brand-loyal or brand-switchers? Which brand did they migrate to, or are they out of the market altogether? Which segments can potentially be won back, and which tactics have previously worked in the past to bring customers back?

Searching For Insights Artists

Of course, finding someone with all of these traits is not easy, especially when the single most important factor to being an insights artist is experience.

In a perfect world, every organization searching for a data scientist would be hiring a former analyst who has spent the last 10 years as a marketing manager. But those people aren’t easy to find. An alternative would be to stop looking for one Renaissance man or woman to do it all – and instead solve this skills/experience combination problem by assembling the right mix of people. Often, the best solutions are derived from collaboration.

When an analyst, data artist, and marketing manager can all come together and understand the value each brings to the equation, success is more easily achieved.

So I propose we kill the data scientist title in favor of the insights artist. In reality, this is most likely a team of traditional roles that organizations have been hiring for years: analysts and marketing managers. The key is to stop isolating them in departmental silos and bring them together, so that each understands the problem, the potential solutions, and the best way to convert massive amounts of data into actionable insights.

 

15 Apr 2015

Published on CNBC

Five years ago, "flash sale" start-ups introduced a new business model into the retail ecosystem: high-end goods, in limited supply, at affordable prices. Led by Gilt Group, Rue La La, and Zulily, these companies played to consumers growing tendency and desire, to impulse buy and changed the way millions of consumers shop on a daily basis.

However, many failed to build long-term loyalty form their user base. If you were a member of one flash-sale site, you were most likely a member of many others. This lack of loyalty forced them to compete on price and product diversity as more players entered the market. 

The new business models currently disrupting retail are adapting and learning from the flash sale model by providing a greater focus on loyalty and multi vertical disruption that the flash sale model lacked.

Subscription commerce

As software-as-a-service disrupted the revenue model of the tech industry, a few genius entrepreneurs determined that the same business model can be applied to products and traditional commerce.

Subscription-commerce companies led by beauty-products site Birchbox and others have brought the concept mainstream, allowing the new batch of entrepreneurs to build and evolve the model. Instead of being tied to the once-a-month delivery cycle, start-ups emerging in the space are focusing on delivering products when and where they are needed, becoming even more advanced in the ability to personalize products and delivery cycles.

However, the real disrupting factor for the subscription-commerce model is if it can displace the products that we buy on a regular basis; the products that, for the past 50 years, consumers have purchased on their weekly or monthly shopping trips. Imagine a scenario where a retailer knew enough about your consumption habits where it could predict when you needed more milk, more cereal or more soap? Chances are, if you have a loyalty card, they already know this and are missing out on a new reliable and loyal revenue stream.

Nordstrom is experimenting in this space with their recent acquisition of personal-shopper site Trunk Club; however the potential goes far beyond apparel. Expect to see some retailer experimentation in the coming year. If not, start-ups like home-products site ePantry will quickly steal market share.

Consumer-to-consumer

Consumer-to-consumer business models are in the process of resurgence; Rather than simply connecting buyers and sellers, today's marketplaces are harnessing new technologies to put a new spin on an age-old process.

Move Loot, a used-furniture marketplace that raised $9 million in new funding this past December, handles all aspects of the transaction process and will coordinate pick-up and delivery of products as well. As brands and retailers look for new ways to engage their customers, an understanding of their product, post initial sale, becomes increasingly important. Not just as a means to better target them for upgrades but as a way to gain control over the product lifecycle.

Expect to see more brands and retailers embracing the resale of their goods as a way to better understand and build loyalty from their customers.

On-demand

The on-demand economy is disrupting many industries but more than anything it is changing consumer's perception of service and reliability. Consumers want here and now and will potentially pay a premium for that convenience. Amazon has been a leader with their Amazon Prime membership, offering free 2 day shipping on the majority of their inventory. 

By delivering goods to the consumer when and where they need them, on-demand business models require greater efficiencies out of the retailer. As consumers seek to become more efficient with their time, the desire to meander and browse the grocery store or shopping mall becomes less appealing. Consumers are much more direct in their shopping habits and retailers will need to adjust.

Part of the adjustment will be streamlined inventory systems. We are seeing retailers leverage the click-and-collect model; utilizing store inventory to fulfill e-commerce orders rather than relying on a centralized warehouse. The next evolution in this model will be to leverage the sharing economy to deliver those goods in a timely and efficient manner.

The uniting factor between all three models is loyalty to the retailer/brand and convenience to the consumer. Start-ups have proven the viability, now we wait to see if the large retailers are nimble enough to react.


Published on CNBC

Five years ago, "flash sale" start-ups introduced a new business model into the retail ecosystem: high-end goods, in limited supply, at affordable prices. Led by Gilt Group, Rue La La, and Zulily, these companies played to consumers growing tendency and desire, to impulse buy and changed the way millions of consumers shop on a daily basis.

However, many failed to build long-term loyalty form their user base. If you were a member of one flash-sale site, you were most likely a member of many others. This lack of loyalty forced them to compete on price and product diversity as more players entered the market. 

The new business models currently disrupting retail are adapting and learning from the flash sale model by providing a greater focus on loyalty and multi vertical disruption that the flash sale model lacked.

Subscription commerce

As software-as-a-service disrupted the revenue model of the tech industry, a few genius entrepreneurs determined that the same business model can be applied to products and traditional commerce.

Subscription-commerce companies led by beauty-products site Birchbox and others have brought the concept mainstream, allowing the new batch of entrepreneurs to build and evolve the model. Instead of being tied to the once-a-month delivery cycle, start-ups emerging in the space are focusing on delivering products when and where they are needed, becoming even more advanced in the ability to personalize products and delivery cycles.

However, the real disrupting factor for the subscription-commerce model is if it can displace the products that we buy on a regular basis; the products that, for the past 50 years, consumers have purchased on their weekly or monthly shopping trips. Imagine a scenario where a retailer knew enough about your consumption habits where it could predict when you needed more milk, more cereal or more soap? Chances are, if you have a loyalty card, they already know this and are missing out on a new reliable and loyal revenue stream.

Nordstrom is experimenting in this space with their recent acquisition of personal-shopper site Trunk Club; however the potential goes far beyond apparel. Expect to see some retailer experimentation in the coming year. If not, start-ups like home-products site ePantry will quickly steal market share.

Consumer-to-consumer

Consumer-to-consumer business models are in the process of resurgence; Rather than simply connecting buyers and sellers, today's marketplaces are harnessing new technologies to put a new spin on an age-old process.

Move Loot, a used-furniture marketplace that raised $9 million in new funding this past December, handles all aspects of the transaction process and will coordinate pick-up and delivery of products as well. As brands and retailers look for new ways to engage their customers, an understanding of their product, post initial sale, becomes increasingly important. Not just as a means to better target them for upgrades but as a way to gain control over the product lifecycle.

Expect to see more brands and retailers embracing the resale of their goods as a way to better understand and build loyalty from their customers.

On-demand

The on-demand economy is disrupting many industries but more than anything it is changing consumer's perception of service and reliability. Consumers want here and now and will potentially pay a premium for that convenience. Amazon has been a leader with their Amazon Prime membership, offering free 2 day shipping on the majority of their inventory. 

By delivering goods to the consumer when and where they need them, on-demand business models require greater efficiencies out of the retailer. As consumers seek to become more efficient with their time, the desire to meander and browse the grocery store or shopping mall becomes less appealing. Consumers are much more direct in their shopping habits and retailers will need to adjust.

Part of the adjustment will be streamlined inventory systems. We are seeing retailers leverage the click-and-collect model; utilizing store inventory to fulfill e-commerce orders rather than relying on a centralized warehouse. The next evolution in this model will be to leverage the sharing economy to deliver those goods in a timely and efficient manner.

The uniting factor between all three models is loyalty to the retailer/brand and convenience to the consumer. Start-ups have proven the viability, now we wait to see if the large retailers are nimble enough to react.

31 Mar 2015