customer segmentation

7月 062017
 

If there’s one thing today’s organisations can agree on, it’s that the world has changed. In the words of Tony Mooney, former managing director of insight and decision science at Sky, speaking at the recent SAS Data & Customer Experience Forum, “we are now living in a world that is volatile, uncertain, ambiguous and complex.”

As our environment has evolved, so have our techniques for understanding, measuring and motivating people and groups.

Struggling to keep up

The modern consumer is transitioning from digital-first to digital-only and they expect every business in every industry to achieve “digital parity.” In other words, your business needs to be as easy to do business with as the best of what your customer has encountered online and in self-service solutions.

 And it’s not just in the digitally native millennial generation where this transition is occurring. These changes are being realised across the generations because customers who aren’t millennials have been influenced by a millennial outlook. As a result of these changes, our expectation of brand responsibility has evolved as has our interaction with brands in a data-driven world.

Over the last decade we’ve seen a plethora of marketing technologies thrust upon us to harness this new world view and at the same time, influence it. From SMS, web analytics, mobile apps, web personalisation, recommendation engines, conversion optimisation platforms . . .the list goes on. The upshot of the investment in these myriad technologies is that it has created many disconnected silos across the organisation, each with their own set of rules and logic, focused on an individual channel and that frequently don’t speak well together. Unfortunately for consumers, the end result is a fragmented and inconsistent experience and marketers find themselves still failing to deliver a stellar customer experience.

Customer experience has been at the core of conversations about engagement for the last few years. The goal? To interact with customers with the most relevant communications at the right time via the right channel. There needs to be understanding of a customer’s attitudes preferences, interests and needs. These must be balanced with an understanding of customer lifetime value, propensity and risk to make accurate and profitable decisions about the right content, the right offer, the right price or the right product. If this can be achieved at the moment of customer engagement, then those brands won’t be the ones that get left behind.

The real-time opportunity

When we are managing outbound communications to consumers, planning email or direct marketing campaigns, we have time to consider all of the inputs from both a customer insight perspective and an internal business perspective before we decide on the most relevant content. But when a customer proactively engages with us, over the web, via an app, with a call centre agent or in person, we have just milliseconds at worst and seconds at best to make the most accurate and profitable decision. This becomes a major challenge.

According to our recent research and speaking to key decision-makers in consumer organisations, one in five believe the ability to interact with customers and adjust those interactions in real-time (based on the most up to date insight and context), would see revenues jump by as much as 20-40 percent. The majority of decision-makers expect revenues to increase by at least 10 percent.

Daragh Kelly, Data Strategy & Innovation Director at Sky, echoed the thoughts of Mooney at the forum, saying the key to achieving this is “improving all of the small decisions that are made by organisations when they interact with customers." Small decisions are those made in response to an individual customer’s choices and a focus on small decisions offers benefits through a multitude of applications:

  • Improving the management of risk and the matching of price to risk.
  • Reducing or eliminating fraud and waste.
  • Increasing revenue by making the most of every opportunity
  • Improving the utilisation of constrained resources across the organisation, all whilst delivering a superior customer experience.

Organisations need to adapt from making decisions at the speed of the organisation to making decision at the speed of the customer.  For instance, if a customer chooses not to engage with an offer online, based on all the information known about that individual including their lifetime value, propensity and attitudes, as well as new contextual information (e.g., their location, the device they’re using, etc.), they can be served a more suitable alternative within seconds.

Planning and process

To remain relevant in increasingly competitive and disruptive markets and to meet the expectations of the modern consumer, organisations need to put a framework in place to enable them to make better "small decisions" at those moment of customer interaction, which are the true "crunch" moments for individual customers.

Permanent TSB is one organisation that has started to implement such a framework. Underpinned by in depth and advanced customer analytics, the organisation has moved from engaging with customers via outbound only calling campaign structure to developing an omni-channel engagement framework. Through customer analytics, the organisation has been able to prioritise activities and deliver services, offers and updates highly tailored for individual customers.

Businesses like Allied Irish Bank have made analytics a key strategic pillar, with buy-in from the C-level down through the organisation. Customer analytics is being used to drive informed and accurate decision-making right across the business.

Consumers don’t think in channels. They just want to do business with you in a way that is easy, consistent and relevant, regardless of how and when they interact with you. This means they expect you to know them as a customer, to understand their previous engagements and transactions with you and to use the data they make available to you. Only then can you deliver a personalised and relevant experience, every time. Broad brush segmentation approaches to customer interactions based on rules and demographics will no longer cut it. Instead we need to get to a segment of one. Making analytical decisions, based on an in-depth understanding of each individual customer and making those decisions at the speed of the customer rather than at the speed of the organisation, is the key to delivering the superior customer experiences now being demanded by all consumers.

Find out more about how data analytics can deliver personalised decisions to customers in real-time.

The age of now: focusing on the segment of one was published on Customer Intelligence Blog.

7月 062017
 

If there’s one thing today’s organisations can agree on, it’s that the world has changed. In the words of Tony Mooney, former managing director of insight and decision science at Sky, speaking at the recent SAS Data & Customer Experience Forum, “we are now living in a world that is volatile, uncertain, ambiguous and complex.”

As our environment has evolved, so have our techniques for understanding, measuring and motivating people and groups.

Struggling to keep up

The modern consumer is transitioning from digital-first to digital-only and they expect every business in every industry to achieve “digital parity.” In other words, your business needs to be as easy to do business with as the best of what your customer has encountered online and in self-service solutions.

 And it’s not just in the digitally native millennial generation where this transition is occurring. These changes are being realised across the generations because customers who aren’t millennials have been influenced by a millennial outlook. As a result of these changes, our expectation of brand responsibility has evolved as has our interaction with brands in a data-driven world.

Over the last decade we’ve seen a plethora of marketing technologies thrust upon us to harness this new world view and at the same time, influence it. From SMS, web analytics, mobile apps, web personalisation, recommendation engines, conversion optimisation platforms . . .the list goes on. The upshot of the investment in these myriad technologies is that it has created many disconnected silos across the organisation, each with their own set of rules and logic, focused on an individual channel and that frequently don’t speak well together. Unfortunately for consumers, the end result is a fragmented and inconsistent experience and marketers find themselves still failing to deliver a stellar customer experience.

Customer experience has been at the core of conversations about engagement for the last few years. The goal? To interact with customers with the most relevant communications at the right time via the right channel. There needs to be understanding of a customer’s attitudes preferences, interests and needs. These must be balanced with an understanding of customer lifetime value, propensity and risk to make accurate and profitable decisions about the right content, the right offer, the right price or the right product. If this can be achieved at the moment of customer engagement, then those brands won’t be the ones that get left behind.

The real-time opportunity

When we are managing outbound communications to consumers, planning email or direct marketing campaigns, we have time to consider all of the inputs from both a customer insight perspective and an internal business perspective before we decide on the most relevant content. But when a customer proactively engages with us, over the web, via an app, with a call centre agent or in person, we have just milliseconds at worst and seconds at best to make the most accurate and profitable decision. This becomes a major challenge.

According to our recent research and speaking to key decision-makers in consumer organisations, one in five believe the ability to interact with customers and adjust those interactions in real-time (based on the most up to date insight and context), would see revenues jump by as much as 20-40 percent. The majority of decision-makers expect revenues to increase by at least 10 percent.

Daragh Kelly, Data Strategy & Innovation Director at Sky, echoed the thoughts of Mooney at the forum, saying the key to achieving this is “improving all of the small decisions that are made by organisations when they interact with customers." Small decisions are those made in response to an individual customer’s choices and a focus on small decisions offers benefits through a multitude of applications:

  • Improving the management of risk and the matching of price to risk.
  • Reducing or eliminating fraud and waste.
  • Increasing revenue by making the most of every opportunity
  • Improving the utilisation of constrained resources across the organisation, all whilst delivering a superior customer experience.

Organisations need to adapt from making decisions at the speed of the organisation to making decision at the speed of the customer.  For instance, if a customer chooses not to engage with an offer online, based on all the information known about that individual including their lifetime value, propensity and attitudes, as well as new contextual information (e.g., their location, the device they’re using, etc.), they can be served a more suitable alternative within seconds.

Planning and process

To remain relevant in increasingly competitive and disruptive markets and to meet the expectations of the modern consumer, organisations need to put a framework in place to enable them to make better "small decisions" at those moment of customer interaction, which are the true "crunch" moments for individual customers.

Permanent TSB is one organisation that has started to implement such a framework. Underpinned by in depth and advanced customer analytics, the organisation has moved from engaging with customers via outbound only calling campaign structure to developing an omni-channel engagement framework. Through customer analytics, the organisation has been able to prioritise activities and deliver services, offers and updates highly tailored for individual customers.

Businesses like Allied Irish Bank have made analytics a key strategic pillar, with buy-in from the C-level down through the organisation. Customer analytics is being used to drive informed and accurate decision-making right across the business.

Consumers don’t think in channels. They just want to do business with you in a way that is easy, consistent and relevant, regardless of how and when they interact with you. This means they expect you to know them as a customer, to understand their previous engagements and transactions with you and to use the data they make available to you. Only then can you deliver a personalised and relevant experience, every time. Broad brush segmentation approaches to customer interactions based on rules and demographics will no longer cut it. Instead we need to get to a segment of one. Making analytical decisions, based on an in-depth understanding of each individual customer and making those decisions at the speed of the customer rather than at the speed of the organisation, is the key to delivering the superior customer experiences now being demanded by all consumers.

Find out more about how data analytics can deliver personalised decisions to customers in real-time.

The age of now: focusing on the segment of one was published on Customer Intelligence Blog.

6月 162017
 

Tiffany Carpenter, head of customer intelligence at SAS UK & Ireland, looks at the benefits of real-time customer experience and offers a preview into how analytics is powering hyper-personalised customer journeys

In recent years, customer experience has become an important battleground for brands. Yet, in a hyper-connected, hyper-competitive environment where it is becoming increasingly difficult to compete on product or price alone, the concept of customer experience has grown in importance as organisations fight to remain relevant and deliver against customer expectations.

Customers expect the organisations they are interacting with to make it easy to business with them. They expect a seamless experience regardless of how they engage with you whether it be online, via an app, a call centre or in person; and they expect their personal information and data that they have made available, to be used appropriately by organisations to deliver relevant experiences.  To deliver against these expectations,  businesses must first fully understand the wants and needs of current and prospective customers. While this may sound simple enough in principle, most organisations are only using a limited amount of data to try to understand their customers. In fact, most UK organisations admit to using less than half of the valuable data available to them, and they will often analyse it using basic tools or spreadsheets that fail to provide a single view of the customer.

Achieving a segment of one

What’s needed is an approach that allows organisations to concentrate on delivering a superior customer experience by achieving relevancy at every touchpoint based on an understanding of each individual customer – a segment of one.

Today’s customers want the call centre to know when they have just been on the website. They want brands to adjust their marketing strategies if they’ve  made a complaint or negatively reviewed a product or service For businesses, this means having access to a ‘central brain’ that can analyse of all the data available in a timely manner with the ability to inject that insight into any customer interaction across any department and channel -  in real-time if necessary.

This means using data about what’s already happened as well as what’s happening now, to predict what’s going to happen in the future, what the best outcomes will be and make profitable and accurate decisions at each point of a customer interaction.

The central brain

In the race to digitalisation, the mistake many businesses make when trying to achieve a segment of one is placing too much emphasis and narrow focus on digital data. Each lifecycle stage, across each channel is important – from initial consideration, to active evaluation, to the moment of purchase and even the post-purchase experience. Key to successful customer intelligence strategies is tying together offline and online data to get a better understanding of the customer.

Rather than analysing data from a single digital transaction or following customers around in a digital world, It’s more important to understand what happens prior, during and after a digital interaction to create a full picture of behavioural insights. To truly understand customer behaviour and deliver the most value at each customer touch point non-digital data such as demographic, psychographic, transactional, risk and many others types of data - that sit both outside and inside the digital environment - needs to be analysed and mapped to specific stages in the customer lifecycle.

More importantly, once businesses gain these insights, they need to consider how they use this insight to make the right decisions that deliver value to the business. Where appropriate those decisions need to be made in real time and injected into the customer interaction channel at the point of engagement. Each stage of the customer journey needs to be viewed as an opportunity to improve the customer experience. And each stage is an opportunity to gain more insight that can be fed back into marketing processes to draw from the next time. Only then can you deliver the right message at the right time via the right channel.

A personalised experience in real-time

Shop Direct is a great example of a business embracing this approach. Its goal was to make it easier for customers to shop with them, thereby improving the customer experience whilst increasing customer spend. As a 40-year-old business that started as a catalogue company, it was sitting on a huge amount of data that had been captured over the years about its customers and they wanted to find a way to use that data to deliver a highly personalised customer experience.

At the time, a customer shopping for jeans on their Very.co.uk website could be presented with 50 pages of options to scroll through. By analysing the existing data Shop Direct is now able to predict which jeans a customer is most likely to be interested in and personalise the customer’s shopping experience. This is done via an individually personalised sort order in real time to show the products they are most interested in first. Harnessing data and advanced analytics to deliver unparalleled levels of personalistion has seen Shop Direct’s profits surge by 43%.

Group CEO at Shop Direct, Alex Baldock, has said that the company is "all about making it easier for our customers to shop. That's why we're passionate about personalisation. We want to tailor everything for our customer; the shop they visit and how we engage with them - before, during and after they’ve shopped."

The survival factor

In the future, developing a superior customer experience will rely on understanding the balance between delivering the right decision in real-time and giving yourself time to make the right decision. It’s crucial to remember that not every decision about the customer experience needs to be managed in real-time. Organisations have huge amounts of data at their fingertips that they can use to predict and plan to shape products, services and messages.

However, there will be moments when a decision needs to be  made in real-time as to what the right content, message, offer or recommendation for an individual customer might be. This decision should not just be based on what area of a website a customer clicked on, or whether they liked your facebook page. To make accurate and profitable decisions requires insight into offline and online historical data. This must be coupled with real time contextual data as well as a clear understanding of business goals and objectives, and clarity around the predicted outcome of each possible decision. To achieve this, businesses must move away from a channel-specific approach with fragmented systems and rules and embrace a centralised analytical decisioning capability. This would have access to all relevant data, a centralised set of logic and rules, and be able to automate complex analytical decisions at scale and push those out to any channel across any business unit at the right time.

This will need to be what underpins the entire business; the organisations that get this right, will be the ones that survive.

For more insights into how analytics is powering today’s hyper-personalised customer journey, come along to the SAS Data and Customer Experience Forum where we will be announcing headline findings from new research exploring where UK businesses are on the journey to delivering a real-time customer experience.

Transforming the customer experience with analytics was published on Customer Intelligence Blog.

6月 162017
 

Tiffany Carpenter, head of customer intelligence at SAS UK & Ireland, looks at the benefits of real-time customer experience and offers a preview into how analytics is powering hyper-personalised customer journeys

In recent years, customer experience has become an important battleground for brands. Yet, in a hyper-connected, hyper-competitive environment where it is becoming increasingly difficult to compete on product or price alone, the concept of customer experience has grown in importance as organisations fight to remain relevant and deliver against customer expectations.

Customers expect the organisations they are interacting with to make it easy to business with them. They expect a seamless experience regardless of how they engage with you whether it be online, via an app, a call centre or in person; and they expect their personal information and data that they have made available, to be used appropriately by organisations to deliver relevant experiences.  To deliver against these expectations,  businesses must first fully understand the wants and needs of current and prospective customers. While this may sound simple enough in principle, most organisations are only using a limited amount of data to try to understand their customers. In fact, most UK organisations admit to using less than half of the valuable data available to them, and they will often analyse it using basic tools or spreadsheets that fail to provide a single view of the customer.

Achieving a segment of one

What’s needed is an approach that allows organisations to concentrate on delivering a superior customer experience by achieving relevancy at every touchpoint based on an understanding of each individual customer – a segment of one.

Today’s customers want the call centre to know when they have just been on the website. They want brands to adjust their marketing strategies if they’ve  made a complaint or negatively reviewed a product or service For businesses, this means having access to a ‘central brain’ that can analyse of all the data available in a timely manner with the ability to inject that insight into any customer interaction across any department and channel -  in real-time if necessary.

This means using data about what’s already happened as well as what’s happening now, to predict what’s going to happen in the future, what the best outcomes will be and make profitable and accurate decisions at each point of a customer interaction.

The central brain

In the race to digitalisation, the mistake many businesses make when trying to achieve a segment of one is placing too much emphasis and narrow focus on digital data. Each lifecycle stage, across each channel is important – from initial consideration, to active evaluation, to the moment of purchase and even the post-purchase experience. Key to successful customer intelligence strategies is tying together offline and online data to get a better understanding of the customer.

Rather than analysing data from a single digital transaction or following customers around in a digital world, It’s more important to understand what happens prior, during and after a digital interaction to create a full picture of behavioural insights. To truly understand customer behaviour and deliver the most value at each customer touch point non-digital data such as demographic, psychographic, transactional, risk and many others types of data - that sit both outside and inside the digital environment - needs to be analysed and mapped to specific stages in the customer lifecycle.

More importantly, once businesses gain these insights, they need to consider how they use this insight to make the right decisions that deliver value to the business. Where appropriate those decisions need to be made in real time and injected into the customer interaction channel at the point of engagement. Each stage of the customer journey needs to be viewed as an opportunity to improve the customer experience. And each stage is an opportunity to gain more insight that can be fed back into marketing processes to draw from the next time. Only then can you deliver the right message at the right time via the right channel.

A personalised experience in real-time

Shop Direct is a great example of a business embracing this approach. Its goal was to make it easier for customers to shop with them, thereby improving the customer experience whilst increasing customer spend. As a 40-year-old business that started as a catalogue company, it was sitting on a huge amount of data that had been captured over the years about its customers and they wanted to find a way to use that data to deliver a highly personalised customer experience.

At the time, a customer shopping for jeans on their Very.co.uk website could be presented with 50 pages of options to scroll through. By analysing the existing data Shop Direct is now able to predict which jeans a customer is most likely to be interested in and personalise the customer’s shopping experience. This is done via an individually personalised sort order in real time to show the products they are most interested in first. Harnessing data and advanced analytics to deliver unparalleled levels of personalistion has seen Shop Direct’s profits surge by 43%.

Group CEO at Shop Direct, Alex Baldock, has said that the company is "all about making it easier for our customers to shop. That's why we're passionate about personalisation. We want to tailor everything for our customer; the shop they visit and how we engage with them - before, during and after they’ve shopped."

The survival factor

In the future, developing a superior customer experience will rely on understanding the balance between delivering the right decision in real-time and giving yourself time to make the right decision. It’s crucial to remember that not every decision about the customer experience needs to be managed in real-time. Organisations have huge amounts of data at their fingertips that they can use to predict and plan to shape products, services and messages.

However, there will be moments when a decision needs to be  made in real-time as to what the right content, message, offer or recommendation for an individual customer might be. This decision should not just be based on what area of a website a customer clicked on, or whether they liked your facebook page. To make accurate and profitable decisions requires insight into offline and online historical data. This must be coupled with real time contextual data as well as a clear understanding of business goals and objectives, and clarity around the predicted outcome of each possible decision. To achieve this, businesses must move away from a channel-specific approach with fragmented systems and rules and embrace a centralised analytical decisioning capability. This would have access to all relevant data, a centralised set of logic and rules, and be able to automate complex analytical decisions at scale and push those out to any channel across any business unit at the right time.

This will need to be what underpins the entire business; the organisations that get this right, will be the ones that survive.

For more insights into how analytics is powering today’s hyper-personalised customer journey, come along to the SAS Data and Customer Experience Forum where we will be announcing headline findings from new research exploring where UK businesses are on the journey to delivering a real-time customer experience.

Transforming the customer experience with analytics was published on Customer Intelligence Blog.

4月 132016
 

All of us we have had the unfortunate experience of going to a store and encountering a salesperson who is unable to give us expert advice about a product or service. It’s not because salesperson is unwilling to help us, but rather because he or she does not know in enough about the products the company sells.

In fact, the Retail in Belgium survey carried out by Vlerick Business School and Insites Consulting revealed that "not less than 44 percent of consumers feel they know more than the seller about [a] product, after searching online information.” I’m sure these numbers are similar in other countries.

Another challenge for in-store sales is managing the peaks and uneven shopping traffic throughout the day, week or year while having enough competent salespeople for floor coverage.

Are brick-and-mortar operators losing ground over what was considered their strength to ecommerce – expert knowledge? Fortunately, it’s not a bleak as it appears. Traditional retailers have options, but they must be innovative and aggressive to challenge current trends.

Data management and analytics to the rescue

We know that shoppers often use the web to research products before visiting a store, but how can retailers add value once shoppers enter the store? That's where contextual marketing play an important role.Albert pic

Recent technologies such as iBeacons and wi-fi tracking enable retailers to recognize and accurately locate customers as they travel through a store. The next step is persuading a customer to download and enable an app that allows a retailer to better understand individual shopping behavior. The enticement for shoppers is that retailers can make in-store offers in real time via push notifications.

For price-conscious shoppers, downloading an app means they won’t miss out on any promotions. For others, the incentive is learning about new products or offering an improved shopping experience. Being able to meet these goals requires detailed knowledge of individual buying motives. Customer segmentation and creating a customer typology will help.

Once your tracking strategies are enabled, centralized data management for phygitals, both physical and digital data sources, will improve the level of service. The app enables a store to recognize when a shopper enters the store, and using the customer’s transactional history and other data (such as recent online research on the company website), the retailer can improve and enhance the customer experience.

For example, using recommendation engines, you can propose related products based on its location in the store. And all this in real time please because in this context, "right time is real time." If you want to know more about how predictive analytics makes offers more relevant, do not hesitate any longer and read the excellent blog post written by my colleague Adrian Carr about the topic.

The application can also be used by customers to request product/service assistance during their store visit. The sales staff can quickly access information about the customer to better respond to their inquiries.

Needless to say, a customer needs to have a positive initial experience with the app or it will become just another unused app on their smartphone.

If you want to find more information about how SAS enhances the customer experience through contextual marketing, have a look at SAS® Real-Time Decision Manager.  You can also look at our Customer Decision Hub approach to managing customer interactions across all channels.

tags: contextual marketing, customer decision hub, customer experience, customer intelligence, customer segmentation, phygitals, real-time decisioning, retail

The role of contextual marketing for in-store sales was published on Customer Intelligence.

8月 222015
 

As mass marketing becomes less common and effective, we get closer and closer to the ideal of the “segmentation of one,” which involves high degrees of personalization. In that environment, businesses must be able to market to customers at an individual level to remain competitive and relevant. However, without customer analytics technologies -- such as predictive modeling, data visualization, information management and segmentation -- marketing to this degree of detail can’t be done efficiently.

If you reach out to her, you'd better make it good.

If you interrupt her, you'd better make it good.

Let’s discuss the why, how and what lies behind marketing to the segment of one.

Why would an organization want to market at this level? Doesn’t it seem a bit creepy or intrusive? The numbers show that the opposite is true. Numerous studies have proven that this type of interactive marketing is more effective, has much higher success rates, costs less to execute and generates more revenue than mass offers.

Mass marketing over traditional channels usually has a success rate of about 3 to 5 percent. Event triggered marketing -- which executes an offer based on a trigger or behavior being performed -- has a success rate of 10 to 20 percent. Right time marketing to the segment of one -- using context, data and analytics -- comes in at a 40 percent success rate.

When done correctly, segmentation of one allows for the delivery of an offer that is hard to refuse. It is so appropriate, relevant and timely that any brand that can deliver at this level of granularity, should, as they will have much higher response rates to the marketing campaigns and programs that they run. Performing correct segmentation allows marketers to deliver individualized, noninvasive customer communications. In order to do that, it’s important to make sure you’re making customers feel known and welcomed while also preserving their privacy.

How do you go about this? Think about an example where a brand could use this capability. Let’s say Joe Consumer sends a tweet using Retailer XYZ's @twitter handle asking if a certain product is in stock. More than likely Retailer XYZ will respond to @joeconsumer via Twitter with an answer. But what if Joe prefers a response via a different channel, perhaps via a text message or phone call? Would Retailer XYZ have the information and software needed to do that? Often they would not, but that's changing.

Organizations are increasingly using customer analytics to make connections that enable higher degrees of personalization. Just imagine if Retailer XYZ could identify Joe based on his social ID (Twitter handle) and it could tie other information in his profile seamlessly to this social ID -- data attributes such as basic customer information, demographic, purchase and transaction history, etc.? In that same scenario, contextual information -- such as digital data it collected when Joe logged onto its website and browsed the product and associated products would provide richer, more relevant insights that improve how Retailer XYZ responds and even becomes proactive.

The segment of one is no longer as elusive as it may have once seemed because of customer analytics -- enabling organizations to cater to customers that are more empowered and connected than ever. They have access to information anywhere, any time – where to shop, what to buy, how much to pay, etc. That makes it increasingly important to predict how customers will behave when interacting with your organization, so you can respond accordingly.

And the deeper your understanding of customers' buying habits and lifestyle preferences, the more accurate your predictions of future buying behaviors will be. And the more successful you will be at marketing to a segment of one by delivering relevant offers that attract rather than alienate customers.


Editor's note:

This content from Jon originally appeared on CMS Wire as "Marketing to the Segment of One is Closer Than it Seems." One technological development that has enabled the Segment of One is big data - much of which is customer data.

Catalina Marketing has honed the use of customer analytics and big data for years to provide personalized coupon offers at retailer point-of-sale environments. You can get more details about the Catalina Marketing story in this blog post, titled How to manage the world’s longest grocery list.

tags: big data, customer analytics, customer segmentation, personalization, segment of one

Getting to the segment of one was published on Customer Analytics.

12月 102014
 

I recently worked with a company (we’ll call them ABC, Inc.) on a customer segmentation strategy. This particular organization has a predefined set of marketing campaigns that they would send to all of their customers. There was no differentiation in the messaging or channel. Accurate targeting - like playing darts.

We created a number of predictive propensity models and teased out some really interesting segments in their customer population based on their likelihood to do something (buy more products, be more loyal, etc.). As in…people who are more likely to be more loyal are (1) over the age of 40, (2) female, and (3) live in an urban area. They also hate direct mail and love shopping on the Internet. You get the point.

In theory, now that I know who’s more likely to do something, I can target that population with more relevant messaging. Ta-da! I have a data-driven marketing strategy! Not so fast…

The NY Times recently posted an article about the trouble with too much segmentation and not enough creative in political campaigns: “The Big Data era of politics has left some campaigns drowning in their own sophisticated advances. They simply cannot produce enough new, effective messages to keep up with the surgical targeting that the data and analytics now allow.

ABC, Inc. was faced with the same problem. We identified four distinct segments in one of the propensity models. To effectively target those segments, each would need different messaging across different channels. The complexity of their marketing campaign strategy just quadrupled! This is a simple example, but you can imagine what happens as they create more propensity models and segments.

There are three main components to a campaign:

  1. The ability to segment your population,
  2. The message and medium, and
  3. Channel or context.

There’s no point in creating segments if you can’t align relevant messaging, media and context. In addition to investments in analytics and technology needed to support segmentation, organizations must equally invest in the message and the medium.

Just because you can create tons of micro-segments doesn’t mean that you need to. In ABC’s case, we combined the propensity scores with the segments so that we could prioritize and identify where we could have the biggest impact. The short-term plan included a series of targeted messaging for two segments, with plans to expand to four in a phased approach. This gave them the time to develop and test new messaging as well as build out their capabilities for managing multiple campaign workstreams.

If you’re just starting to use segmentation strategies in your marketing programs, don’t overwhelm yourself with complexity. As you identify the relevant segments in your business, look for high-impact opportunities, but remember that your creative messaging will make the difference. As a political campaign director in the Times article said:

“We’re at the point where everyone can afford the Ferrari
[the data and the tools] –
it’s a question of  who’s the better driver
[the creative message].”

And the good news is that you don't have to choose. Make sure you have the Ferrari, and be the better driver. Let me know what you think.

tags: big data, Campaign Management, customer segmentation
5月 072014
 

What does a day in the life of an ad agency look like? In Don Draper’s Mad Men world, it involved creative brainstorming and, yes, a lot of smoking and drinking at the office. Much has changed since the 1960s. With the exponential increase in digital data, today’s agencies are faced with a Big Data dilemma.

In addition to their creative roles, agencies – and modern marketers – are acquiring customer data from multiple sources: Internal and external data, data from their CRM systems and social media chatter. They’re mining partner, supplier, public and commercial data to get a more accurate and single view of the customer. And they are looking at something Gartner defines as “dark data” -- the data gathered from blogs, texts, clickstreams, speech, location and context. All of this adds up to equal mind-blowing amounts of data. But when agencies – and marketers alike – focus on the growing availability of that data and not just the sheer magnitude, several opportunities rise to the surface.

At a recent conference with some of the leading advertising agencies in New York, I heard a few areas where these companies need to put this Big Data to work in order to:

  1. Enhance the customer experience
  2. Segment customers
  3. Automate campaign reports

Enhance the customer experience

Some of the ad agencies at the event lamented about the manual processes and the data challenges that have slowed them down in the past. With the tremendous growth of data, many of them are stuck using outdated products to mine, sort and optimize lists and datasets. But the old programs are quickly being replaced by modern technology that allows them to address online and offline customer challenges such as historical data, CRM data, enrichment data and current session data. The knowledge gained from this influx of data also helps marketers build an individual behavior record over time. At the end of the day, the phrase “It’s all about the customer,” means companies must act faster and smarter to make and keep connections.

Segment customers

The next logical step in modernization is taking the new ways of consuming this Big Data and applying it to current and potential customers. Television might show brainstorming for the perfect mass-media campaign as the only activity done by ad agencies. But today’s agencies need to be multi-faceted and show they are true partners with their clients for a variety of marketing activities, including customer segmentation.

With decreased budgets and resources, the answer isn’t to increase the amount of campaigns, but rather make them more effective. This can be achieved by better targeting the customers within a campaign. Because all prospects aren’t created equal, they will respond differently to your outreach -- some will respond to email, others will respond to a digital advertising and you might have some that will only respond to an in-person meeting. Understanding how to connect with your targets is critical.

If email marketing is your campaign vehicle of choice, don’t just blast a single email with a gated offer to all of your existing customers. It’s much more effective to send a series of targeted emails -- such as a lead nurturing campaign -- with unique content for each segment. Measure success by clicks and conversions, and make changes based on those results.

Automate campaign reports

The third challenge facing agencies today is automating campaign reports for clients. The ideal here is to use a comprehensive marketing automation solution, but no matter the approach a key starting point is to focus on data quality and data integration. Both are important because data must be pulled, integrated and cleansed from many different sources – many of them big data sources. For maximum usefulness, the reports need to be consumable by clients.

Again, technology can play an important role here. Finding a solution that is powerful enough to extract data from virtually unlimited sources but is also robust enough to analyze what is contained in the data is a must.  With the SAS Data Management solution you can access your data no matter where it’s stored.  That data is then prepared for reporting and distribution using SAS BI reporting solutions.  The real benefit comes in automating the entire process from beginning to end.

How to channel Don Draper with data

Even if you aren’t pitching a national media campaign to Montgomery Ward in a smoke-filled room, like Don Draper might, or to Target in a modern, glass-walled conference room, seeing the opportunities that come from the availability of big data can be a powerful asset.

Pair the data with cutting-edge technology that lets you mine social media data to quickly determine the most important topics for a client’s brand. Use ad hoc exploration and visualizations to quickly identify key brand associations. Score sentiment by topic to understand exactly why customers love or hate your brand. Produce clear evidence why the client should choose your recommended marketing strategy. Once you do this, you’ll be well on your way to making a mark on Madison Avenue.

Thank you for following. Please leave a comment with your thoughts.

tags: big data, customer segmentation, data integration, data management, data quality, lead nurturing, marketing automation
12月 182013
 
Why San Francisco? The Golden Gate Bridge. The Aquarium of the Bay. The best Ramen Noodles. Need more? Our Business knowledge Series offers you four more great reasons to visit San Francisco soon. Data Mining Techniques: Theory and Practice Customer Segmentation Using SAS Enterprise Miner SAS Functions by Example Survival [...]
11月 192013
 
The "Members Only" jacket in the 1980s was the ticket to coolness.

John Balla circa 1982 thinks his "Members Only" jacket makes him look cool.

Gilt is an online retailer based in the United States, founded in 2007 and is best known for flash sales - only available to members for 36-48 hours. It's all about giving its members the inside scoop to snag something cool and sought after, and then adding the thrill of getting it for a bargain. It's about limited quantities for a limited time. And with 6 million members, it's a clearly compelling mix.

Their mix starts with sought-after products – often luxury goods not normally found online. Then they offer them in limited quantities at big discounts to an exclusive audience and only for a limited time. And they do it over and over again. You can't even see what's on sale unless you're a member. New sales often seem like a trunk sale at your favorite boutique, featuring merchandise from a single brand or small groups of brands.

Their members-only exclusivity certainly promotes loyalty, but that doesn't mean they can rest on their laurels. In fact, Gilt has the inside track on loyalty by proactively cultivating it with marketing analytics. And they'd have to be - as an online retailer, they’re in the thick of digitally-savvy, empowered customers and an increasingly competitive market.

Gilt's forward-looking approach is what keeps them in the know – by utilizing real-time, predictive analytics that prompt tailored, timely interactions that deepen brand relationships and fuel long-term loyalty. Their sophisticated use of analytics includes techniques to gain deep customer understanding through data mining, implicit data collection and third-party data appends with traditional sources of insight, such as surveys and focus groups. Other approaches include persona-based segmentation, affinity scoring and lifetime value analysis to guide how they target, acquire and engage with high value customers.

Gilt’s best customers clearly understand value, and
Gilt clearly knows how to value them.

Want the members-only view of how they do it?  Join us on November 21, 2013 at 1:00pm ET for a webinar produced by Loyalty360 called, Building Loyalty with Digitally-savvy, Empowered Customers.\

If you’re unable to tune in live, we’ll offer a recording afterward on demand at sas.com. Stay tuned for that update.

tags: customer segmentation, marketing analytics, online marketing, real-time decisioning, retail