customer data

3月 092018
 

Eidtor's note: Andrew Fowkes, Head of Retail Centre of Excellence at SAS UK & Ireland, explores the factors driving some retailers to excel and others to fail in a complex environment A stark polarisation is now emerging between winners and losers on the high street. Companies that have focused on [...]

Three things retail winners are doing right now was published on Customer Intelligence Blog.

2月 202017
 

Marketers today use varying adaptations of the customer journey to describe a circular, looped decision pathway with four distinct phases.

Mapping the right data to specific stages of the customer journey is all about getting to know your customers and developing initiatives to put that knowledge into action. Applying analytical models across the key customer journey phases uncovers opportunities to cultivate value generating behaviors and extend the customer’s lifetime value.

  • Initial Consideration Set (Research/Discover). Data and analytics in this phase help you gain deeper customer understanding of customers and prospects. Segmentation surfaces stated and unmet customer needs and buying motivations. Reach the right prospects with look-alike acquisition models and evaluate prospects with lead scoring techniques.
  • Active Evaluation (Explore/Consider). Data and analytics in this phase help you dynamically adapt marketing efforts to customer response – in real-time. Offer optimization techniques can match the appropriate offer based on historical customer response. Amazon’s recommendation engine is a familiar example. Also, A/B and multivariate testing can assess various marketing variables, such as messaging and content types before you roll out initiatives on a wider scale.
  • Moment of Purchase (Buy/Convert). Data and analytics help you understand how and when customers will purchase. Predictive techniques such as propensity models help marketers predict the likelihood that a customer will respond to a specific offer or message and convert. Expand share of wallet with cross-sell and affinity models; or, understand future buying behavior through propensity models.

Post-purchase experience (Use/Maintain/Advocate). Data and analytics in this phase help you uncover patterns of usage behavior and further drive customer engagement. For example, a retail site may tell you the status of your recent order the moment you land on the home page. Churn models such as uplift modeling and survival analysis can provide early warning signs of defection. Preempt customer churn with corrective actions, such as special offers or free upgrades.

Open, unified capabilities needed

Brands that build the most effective customer journeys master three interrelated capabilities: unified customer data platforms, proactive analytics and contextual interactions.

  • Unified customer data platforms: This capability unifies a company's customer data from online and offline channels to extract customer insights and steer customer experience. This includes the ability to cleanse, normalize and aggregate data from disparate systems – within the enterprise and externally – at an individual level.
  • Proactive analytics: Purpose-built data collection and analytics capabilities that incorporates both customer analytics (give brands the customer insight necessary to provide offers that are anticipated, relevant and timely) and marketing analytics (evaluate marketing performance using metrics, such as ROI, channel attribution, and overall marketing effectiveness).
  • Contextual interactions: This capability involves using real-time insights about where a customer is in a journey digitally (browsing product reviews) or physically (entering a retail outlet) or to draw her forward into subsequent actions the company wants her to pursue.

The results are dramatic when marketers can combine data management, analytics and insights execution into unified marketing platform.

Consider gourmet gift retailing icon, Harry & David. By combining data-driven marketing with enriched customer insight, the company transformed its catalog heritage into a contemporary, digital retailing powerhouse. In the past three years, customer retention has increased by 14 percent and sales per customer have gone up 7 percent.

The largest retail group in Switzerland, Migros, used data and analytics to further optimize the customer journey.

The upshot: Change perception to reality

“If change is happening on the outside faster than on the inside the end is in sight.” – Jack Welch

Digitally-empowered prospects and customers are calling the shots, going after what they want when they want it. With a unified view of data and analytics, brands can position themselves in front of their customers’ paths as they navigate the customer journey.

For the brands that can see the world as their customers do – and shape the customer journey accordingly--the reward is higher brand preference, revenue and cost improvements, and a lasting competitive advantage.

Assess your marketing confidence

Take stock of your digital marketing approach with the Marketing Confidence Quotient. This assessment tool quickly identifies and scores your company's strengths and weaknesses across four marketing dimensions: data management, analytics use, process integration and business alignment. It's like having your own personal marketing adviser.

A better approach: Align data and analytics across the customer journey was published on Customer Intelligence Blog.

12月 162016
 

We've been saying that the customer is queen or king for quite some time now. And in the coming year, that will be truer than ever. The customer determines where he or she finds information and which channel and which supplier gets the sale. And there is an abundance of these suppliers (certainly online). Customer loyalty, it seems, is as good as dead. Yes, of course, we are faithful to our local baker and tailor, but for items we don't buy everyday and where there is no personal relationship with the supplier (nor does there always need to be one), we don't really care where we order from. Right?customer loyalty

Today, many consumers make their choice based on only two criteria: price and reviews – the latter providing some confidence about product quality and supplier reliability. And it's an obvious choice. Why would you pay top price for an OEM device charger that you can get from a Chinese web shop for a fraction of the price – unless you need it tomorrow, of course? Virtually no supplier has a monopoly today, and you can switch to a new supplier with just one mouse click.

So does that leave all companies having to compete solely on price? No, that would create an unhealthy market situation. Aiming for good reviews is a great idea, of course, but is merely a partial solution. To encourage customer loyalty in the long term, you need to focus heavily on the last touch point in the customer journey. The three elements are essential in these efforts: data, analytics and real-time decisioning.

Determining the right data

Customers leave a data trail behind in various channels. This data enables you to build up a wealth of information about the customer. This is nothing new, but I have noticed that a lot of companies have difficulty in determining what data from this data stream they should add to the customer profile. By analysing the data, you can determine whether data can be assigned as a fixed value to the customer, or is of only temporary relevance, such as a location, for example. In addition, you can really get to know your customer by analysing this data, using this knowledge to predict behaviour and responding to this behaviour in real time.

Predicting behaviour

Using analytics to predict customer behaviour is the key to success in the last step of the customer journey. In this way, you can create the ultimate balance between customer service-driven interactions and marketing and sales-driven interactions. Just think how valuable it would be to know at this last touch point whether you should persuade the customer with your service, or use a combination offer with a product from the same line?

Helping customers make decisions in the moment

By using data strategically, you can predict where the customer has a need. You know what motivates him to actually make a purchase at that critical decision point. Responding smartly to this will increase customer satisfaction and make those customers more loyal. As a result, you will see that price and reviews are indeed important, but that customers still need a supplier who knows and recognises them, and responds to their needs.

To learn more about creating fiercely loyal customers, download our free ebook, Keep them coming back: You guide to building customer loyalty with analytics.

tags: customer data, customer experience, customer journey, customer loyalty, predictive analytics, Predictive Marketing, SAS Customer Intelligence 360

How do you revive customer loyalty in the digital age? was published on Customer Intelligence.

6月 292016
 

In my first post, I discussed the importance of brand equity and its relationship to good customer experience.

Consider this scenario of an organization where brand equity was negatively impacted by a fractured customer experience. In this case the “brand” is the corporate brand.

Internally, employees knew that the company was in trouble because:

  • It did not have a clear, complete picture of customers.
  • Each business area had their own definition of the customer based on their own partial data.
  • The marketing group targeted middle-aged, price-sensitive customers.
  • Advertising bought media that was targeted to younger audiences.
  • Merchandising targeted affluent households.
  • Customer service had no customer information.
  • Stores, catalog and Internet channels had different marketing programs.
  • Digital channels interacted with customers based on their narrow view of the customer.
  • Data was not shared, so no one had a complete picture of customers.
  • Marketing programs were not coordinated.

Needless to say, this negatively impacted customer experience. Customers were showing up in the stores holding two or three 183061092different promotions valid for that week. Confusion reigned as neither customers or employees were sure which promotions were good in which channel, or which could be used in combination.

The customer experience was a negative one, and marketing response rates declined as did sales and perception of the brand. It did not take long for Wall Street to figure out there were deep problems and the stock price sank.

The Turnaround

What saved this brand?

  • A unified view of the customer.
  • Shared customer insights.
  • Transparency of marketing processes.

The impetus was a turnaround CEO with a maniacal focus on customer and transparent coordination of processes around customer.

Actions

  • His first order of business was to accelerate an already in-progress effort to consolidate customer data across the organization.
  • He made data accessible to all business groups and channels for the tactical customer interaction decisions.
  • For strategic decisions, he demanded an analysis to clearly identify and profile the best and next-best customers. He then required every decision be aligned with these customers.
  • Every business area and every channel needed to show how their resources were being allocated to align with the various customer segments.
  • Interactive channels needed to show how they were supporting consistent messaging to various customer segments and using data to personalize the experience.

Results

  • For the first time, there was transparency of advertising and marketing promotions across all channels.
  • For the first time, business groups were aligned and had a coordinated message to communicate brand value to customers.
  • Customers saw the same messaging across all channels.
  • Customers understood what the brand stood for.
  • Over the next few years, market share increased, stock price soared 800 percent.
  • Employees were confident in their decisions and proud to work for the brand.

This scenario is a great learning experience of what can go right with a brand by consolidating enterprise-wide customer data, and providing transparency across business groups and marketing programs.

Management needs visibility into company-wide plans to make sure that budgets, creatives and programs all support the overall business strategy and the customer experience.

SAS has strong marketing resource management capabilities that are completely integrated with marketing execution capabilities as well as performance metrics. For example, SAS Marketing Operations Management provides the ability to plan, manage and share programs across your SAS Customer Intelligence 360 platform gives you the ability to put those plans into action and engage with customers.

Epilog: Turnaround of the turnaround

Unfortunately, for the organization mentioned above, all the good was undone when a new CEO came in and decided that the current customers were not important for the direction he wanted to take the company. He changed pricing and promotions, corporate logo, store layouts and ditched strong product brands that current customers were loyal to. He severely eroded brand equity among current customers. He insisted that his changes would bring in younger, hipper customers. But it did not because the brand was not one those younger customers valued – no brand equity. That CEO did not last long but the damage was done. The company is now trying to recover from a massive debt burden and damage to its brand equity.

Hope for the future

In our scenario, the current CEO grounds every decision in data and information – not intuition and we will be able to tell a good story of recovery in the future.

tags: brand, brand equity, customer data, SAS Customer Intelligence 360, SAS Marketing Operations Management

Data can help revive brand equity was published on Customer Intelligence.

6月 292016
 

In my first post, I discussed the importance of brand equity and its relationship to good customer experience.

Consider this scenario of an organization where brand equity was negatively impacted by a fractured customer experience. In this case the “brand” is the corporate brand.

Internally, employees knew that the company was in trouble because:

  • It did not have a clear, complete picture of customers.
  • Each business area had their own definition of the customer based on their own partial data.
  • The marketing group targeted middle-aged, price-sensitive customers.
  • Advertising bought media that was targeted to younger audiences.
  • Merchandising targeted affluent households.
  • Customer service had no customer information.
  • Stores, catalog and Internet channels had different marketing programs.
  • Digital channels interacted with customers based on their narrow view of the customer.
  • Data was not shared, so no one had a complete picture of customers.
  • Marketing programs were not coordinated.

Needless to say, this negatively impacted customer experience. Customers were showing up in the stores holding two or three 183061092different promotions valid for that week. Confusion reigned as neither customers or employees were sure which promotions were good in which channel, or which could be used in combination.

The customer experience was a negative one, and marketing response rates declined as did sales and perception of the brand. It did not take long for Wall Street to figure out there were deep problems and the stock price sank.

The Turnaround

What saved this brand?

  • A unified view of the customer.
  • Shared customer insights.
  • Transparency of marketing processes.

The impetus was a turnaround CEO with a maniacal focus on customer and transparent coordination of processes around customer.

Actions

  • His first order of business was to accelerate an already in-progress effort to consolidate customer data across the organization.
  • He made data accessible to all business groups and channels for the tactical customer interaction decisions.
  • For strategic decisions, he demanded an analysis to clearly identify and profile the best and next-best customers. He then required every decision be aligned with these customers.
  • Every business area and every channel needed to show how their resources were being allocated to align with the various customer segments.
  • Interactive channels needed to show how they were supporting consistent messaging to various customer segments and using data to personalize the experience.

Results

  • For the first time, there was transparency of advertising and marketing promotions across all channels.
  • For the first time, business groups were aligned and had a coordinated message to communicate brand value to customers.
  • Customers saw the same messaging across all channels.
  • Customers understood what the brand stood for.
  • Over the next few years, market share increased, stock price soared 800 percent.
  • Employees were confident in their decisions and proud to work for the brand.

This scenario is a great learning experience of what can go right with a brand by consolidating enterprise-wide customer data, and providing transparency across business groups and marketing programs.

Management needs visibility into company-wide plans to make sure that budgets, creatives and programs all support the overall business strategy and the customer experience.

SAS has strong marketing resource management capabilities that are completely integrated with marketing execution capabilities as well as performance metrics. For example, SAS Marketing Operations Management provides the ability to plan, manage and share programs across your SAS Customer Intelligence 360 platform gives you the ability to put those plans into action and engage with customers.

Epilog: Turnaround of the turnaround

Unfortunately, for the organization mentioned above, all the good was undone when a new CEO came in and decided that the current customers were not important for the direction he wanted to take the company. He changed pricing and promotions, corporate logo, store layouts and ditched strong product brands that current customers were loyal to. He severely eroded brand equity among current customers. He insisted that his changes would bring in younger, hipper customers. But it did not because the brand was not one those younger customers valued – no brand equity. That CEO did not last long but the damage was done. The company is now trying to recover from a massive debt burden and damage to its brand equity.

Hope for the future

In our scenario, the current CEO grounds every decision in data and information – not intuition and we will be able to tell a good story of recovery in the future.

tags: brand, brand equity, customer data, SAS Customer Intelligence 360, SAS Marketing Operations Management

Data can help revive brand equity was published on Customer Intelligence.

4月 212016
 

Generating rich customer insights – the centerpiece of successful marketing efforts – is more arduous and crucial in today’s digitally saturated world. Brands must not only understand their customers across all touch points, but analyze and glean patterns from their behavior, and quickly respond to the faintest signs of changing preferences and needs.

 Our multi-screen world creates even more complexity for the marketer. A recent Nielsen study revealed that the typical US consumer now owns four digital devices, and spends 60 hours a week consuming content across devices.

Plus, a majority of US households now own web-connected televisions, computers and smartphones. Amidst all these digital devices, consumers also have numerous choices for how and when they access and engage with that content as part of their customer journey.

Smoother customer journeys, not fragmented hops

Given the growing number of digital touch points where customers now interact with companies, marketing often can’t do what’s needed all on its own. Many brands typically think of customers (and the insights gleaned from them) as being “owned” by particular function – marketing owns brand management; service 483134143owns support; sales owns customer relationships; retail operations own the in-store experience, etc.

As a result, the customer data and corresponding insights are fragmented across these functions. When businesses can’t effectively combine customer insights across multiple digital channels, let alone across multiple customer-facing functions, marketers are less confident about their efforts.

This is why brands must have effective technologies and processes in place so they do not lose track when charting, designing and measuring the customer journey. Whether customers are browsing your brand website, completing a purchase on your mobile app or talking with a service representative via online chat, customers demand to be recognized and treated consistently no matter the channel.

Broader, deeper customer knowledge

To this end, SAS 360 Discover goes beyond channel-level data to collect detailed customer-level data for deeper customer understanding and better marketing decisions. SAS 360 Discover is part of the new SAS Customer Intelligence 360 suite that can help you create a new level of customer experience.

Now, you can go beyond page views and clicks to knowing why customers behave as they do on your digital properties, what are the characteristics of your most profitable customers and which digital interactions successfully resulted in loyal, profitable relationships?

In today’s marketing environment, brands gain a competitive edge if they stop perceiving customer engagement as a series of discrete interactions and instead see it as customers do: a set of interrelated interactions that, when combined, make up the customer experience.

 

tags: customer data, customer experience, digital marketing, omnichannel, SAS 360 Discover, SAS Customer Intelligence 360

SAS 360 Discover: Elevating the role of customer insights for confident digital marketing was published on Customer Intelligence.