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Customer Science Blog

By Justin Petty

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.

 

By Justin Petty

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

By Kyle Fugere

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.

By Kyle Fugere

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

By Julian Highley

The new year has well and truly passed us and so too have the plethora of companies shouting about “the trends to watch out for in 2015!”. While the voices clamouring about this year’s trends have fallen silent, the trends themselves will continue to make their presence felt – well into the future. It’s an oxymoron to talk about “trends” for a single year. Trends should have longevity to justify significant investment. If you’ve been lucky enough to ride the coat-tails of a short-lived fad, great; however for trends to be useful and form a basis for strategy, retailers and brands should be looking at a multi-year time horizon.

Our ‘2020’ trends series will explore in depth the opportunities presented to retailers and brands through nine important trends. As we help retailers and brands navigate the waters of consumer insight, part of our role is to identify the trends impacting customer behaviour. These are the foundation upon which to build strategies to drive loyalty and growth.  But how do you spot a truly useful trend, and more importantly, how can you be sure it will impact customer behaviour in the retail environment?

We humans are creatures of habit – what drives and motivates us stays fairly constant – it’s the context in which we live which shapes change and drives trends.  Human needs are the filter we use to determine what is a useful trend – and the nine trends we have identified as significantly influential all tap into basic human needs and desires. From convenient solutions to make busy lives easier, to personalised products and services to help consumers feel unique.

Over the coming months we will be taking a deep dive into each of these nine trends. In the meantime, get introduced to them through our new report.  Click here to download your copy.

By Julian Highley

The new year has well and truly passed us and so too have the plethora of companies shouting about “the trends to watch out for in 2015!”. While the voices clamouring about this year’s trends have fallen silent, the trends themselves will continue to make their presence felt – well into the future. It’s an oxymoron to talk about “trends” for a single year. Trends should have longevity to justify significant investment. If you’ve been lucky enough to ride the coat-tails of a short-lived fad, great; however for trends to be useful and form a basis for strategy, retailers and brands should be looking at a multi-year time horizon.

Our ‘2020’ trends series will explore in depth the opportunities presented to retailers and brands through nine important trends. As we help retailers and brands navigate the waters of consumer insight, part of our role is to identify the trends impacting customer behaviour. These are the foundation upon which to build strategies to drive loyalty and growth.  But how do you spot a truly useful trend, and more importantly, how can you be sure it will impact customer behaviour in the retail environment?

We humans are creatures of habit – what drives and motivates us stays fairly constant – it’s the context in which we live which shapes change and drives trends.  Human needs are the filter we use to determine what is a useful trend – and the nine trends we have identified as significantly influential all tap into basic human needs and desires. From convenient solutions to make busy lives easier, to personalised products and services to help consumers feel unique.

Over the coming months we will be taking a deep dive into each of these nine trends. In the meantime, get introduced to them through our new report.  Click here to download your copy.

25 Mar 2015

By Emilie Kroner

Published on Mediapost

When I was a child, I loved shopping with my mother at our local Hallmark retailer. I could always count on my mom to never miss a birthday or a special occasion — whether it was for family or a close friend. Deep to her Southern roots and despite having three children and working full-time, she’d have a birthday or Valentines’ Day card for me, and I cherished knowing that. When she walked into our Hallmark, I remember her interacting with their associates — they knew her and they knew me. But not only was there a connection and a relationship between my mom and the Hallmark associates, they knew what she wanted; they knew how to ask the right questions, they knew how to best serve her needs. 

In today’s shopping environment, I’m lucky if a sales associate even greets me at many of the retailers that I frequent. Not because retailers don’t care about me as a customer, but as the competitive marketplace has continued to explode, retailers have had to get smarter around cost efficiencies and labor challenges. Unfortunately, the operational workforces have more responsibility, less training, and fewer opportunities to serve their customers and make crucial relationships, which has significantly changed the level of personal service that you or I as customers receive. 

It’s ironic: In the age of personalization, have we lost our ability to get personal at the store level? 

We don’t have to. We have an extraordinary opportunity to bring the power of personalization in the age of customer data, to the people, but that requires us to make smarter and clear strategic choices; change the structure and organization to ensure teams are able to deliver to the customer, and ensure that, as leaders, we are creating a culture that empowers, rewards, and provides our teams with the opportunities to learn and grow — all with the customer in mind.

Many of today’s strongest organizations differentiate themselves by ensuring that their business is structured and supported to constantly deliver to the customer. From the initial interview process at Zappos, employees are screened to make sure they have the values and passion around customer service. Baristas at Starbucks are educated and tested on all products so that they can educate customers as well as make recommendations. Ritz Carlton employees are empowered to provide great personal experiences to customers, with limited parameters. Nordstrom trusts their employees to deliver great experiences by using their “best judgment in all situations.” 

For most companies, the people who have a direct ability to change the way customers think about the brand comprise over 98% of an organization. so why aren’t we focusing more on them? After all, imagine that each of your 10,000 customers can help only one customer a week to buy one more item at a $5 AUR (average unit retail), resulting in a $2.6M incremental sales lift. Sounds like a pretty solid investment for relatively small changes. 

I say we start using the vast amounts of consumer data we have to start truly transforming the way we deliver to customers. The key is pushing this knowledge down to the front lines and getting the customer information to those who day-in and day-out have the ability to impact the customer experience within minutes. 

Using data, we can discover what customers want and make internal customer promises to stay focused on what matters most to customers. Brands and retailers must hold themselves accountable as a business to these promises,  making them the cornerstone to business strategies. 

  • Educate your business on what’s important to customers and how to use emotional intelligence to deliver personalized experiences. 
  • Reward great customer-focused behavior – not just strong sales results. Lead with a customer focus – consistently communicating the importance of the customer in your strategy. 
  • Equip your store teams with the data to make decisions and do what’s best for your customers – after all, they know the customer better than anyone. 

While it may not be realistic to get back to the personalized model of the “mom and pop” stores, the data is there to help us get closer to our customer in a number of ways that are important to them, and that will ultimately help build loyalty with them. As business leaders, the onus is on us to make the data accessible to everyone in the organization, as an integrated part of our culture.

By Emilie Kroner

Published on Mediapost

When I was a child, I loved shopping with my mother at our local Hallmark retailer. I could always count on my mom to never miss a birthday or a special occasion — whether it was for family or a close friend. Deep to her Southern roots and despite having three children and working full-time, she’d have a birthday or Valentines’ Day card for me, and I cherished knowing that. When she walked into our Hallmark, I remember her interacting with their associates — they knew her and they knew me. But not only was there a connection and a relationship between my mom and the Hallmark associates, they knew what she wanted; they knew how to ask the right questions, they knew how to best serve her needs. 

In today’s shopping environment, I’m lucky if a sales associate even greets me at many of the retailers that I frequent. Not because retailers don’t care about me as a customer, but as the competitive marketplace has continued to explode, retailers have had to get smarter around cost efficiencies and labor challenges. Unfortunately, the operational workforces have more responsibility, less training, and fewer opportunities to serve their customers and make crucial relationships, which has significantly changed the level of personal service that you or I as customers receive. 

It’s ironic: In the age of personalization, have we lost our ability to get personal at the store level? 

We don’t have to. We have an extraordinary opportunity to bring the power of personalization in the age of customer data, to the people, but that requires us to make smarter and clear strategic choices; change the structure and organization to ensure teams are able to deliver to the customer, and ensure that, as leaders, we are creating a culture that empowers, rewards, and provides our teams with the opportunities to learn and grow — all with the customer in mind.

Many of today’s strongest organizations differentiate themselves by ensuring that their business is structured and supported to constantly deliver to the customer. From the initial interview process at Zappos, employees are screened to make sure they have the values and passion around customer service. Baristas at Starbucks are educated and tested on all products so that they can educate customers as well as make recommendations. Ritz Carlton employees are empowered to provide great personal experiences to customers, with limited parameters. Nordstrom trusts their employees to deliver great experiences by using their “best judgment in all situations.” 

For most companies, the people who have a direct ability to change the way customers think about the brand comprise over 98% of an organization. so why aren’t we focusing more on them? After all, imagine that each of your 10,000 customers can help only one customer a week to buy one more item at a $5 AUR (average unit retail), resulting in a $2.6M incremental sales lift. Sounds like a pretty solid investment for relatively small changes. 

I say we start using the vast amounts of consumer data we have to start truly transforming the way we deliver to customers. The key is pushing this knowledge down to the front lines and getting the customer information to those who day-in and day-out have the ability to impact the customer experience within minutes. 

Using data, we can discover what customers want and make internal customer promises to stay focused on what matters most to customers. Brands and retailers must hold themselves accountable as a business to these promises,  making them the cornerstone to business strategies. 

  • Educate your business on what’s important to customers and how to use emotional intelligence to deliver personalized experiences. 
  • Reward great customer-focused behavior – not just strong sales results. Lead with a customer focus – consistently communicating the importance of the customer in your strategy. 
  • Equip your store teams with the data to make decisions and do what’s best for your customers – after all, they know the customer better than anyone. 

While it may not be realistic to get back to the personalized model of the “mom and pop” stores, the data is there to help us get closer to our customer in a number of ways that are important to them, and that will ultimately help build loyalty with them. As business leaders, the onus is on us to make the data accessible to everyone in the organization, as an integrated part of our culture.

24 Mar 2015