Tag Archives: advanced analytics

Analytics, Big data, SAP

Predictive Analytics and the Segment of One

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by Richard Mooney,                                           Product Manager, Advanced Analytics, SAP

 

Woman Buying Clothes --- Image by © Tim Pannell/CorbisOne of the areas that SAP is investing heavily in is the idea of providing ‘extreme customer experience’ to the ‘Segment of One.’  What does this mean for analytics? Traditionally, large enterprises split customers into multiple segments based on customer attributes that were then used to identify and classify customers.  These segments included their location, their current and potential spend, and which products and options they chose when they became a customer.

Marketers use these segments to determine which products they would market to which customers. Likewise, customer support applies different levels of service to each customer segment, and operations measures the profitability of each segment separately.

This is both highly frustrating to customers and an incredibly inefficient use of resources.

  • Every customer is different. They feel frustrated when their individual needs aren’t met, and their expectations about how they’re treated as customers are rising.
  • A one-size-fits-all approach doesn’t take into account the emerging customer acquisition and support channels that provide the potential to reduce the cost of service and market much more effectively. This includes mobiles applications, social networks, and the internet of things.
  • Because the cost of customer communication is plummeting, customers are inundated with content. They’re choosing to delete, unfollow and unsubscribe from content that doesn’t speak to them.

These same trends are opportunities. Companies are collecting far more information than ever before and the technology exists to leverage this at scale.  They no longer need to treat customers as being pure segments.  They can market to them personally, understand their likes and preferences, and give them services, all of which turns them into fans and advocates.

So How Do We Use Data to Connect to the Segment of One?

  • Make the Segment of One a corporate mandate. Communicate and service each customer as if it were a personal connection.
  • Rethink how your digital front office assets (including digital marketing, customer service and online) interact with customers to support this mandate.
  • Build a team of data scientists and data analysts to move from guesswork to data-driven decision making.
  • Build your customer communication around their analysis and deploy their work into every front office application. Measure and monitor the return on investment (ROI) from each initiative.

Done properly, this will result in happier customers and higher net promoter scores.   It also means that the data companies are collecting results in visible ROI, which improves their bottom line.

We would love to hear your thoughts on how the Segment of One will drive your data strategy.  Contact us or comment here to let us know.

 

Analytics, SAP, Uncategorized

What you should consider when embarking on an Advanced Analytics journey?

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By Paul Pallath, PHD,  Chief Data Scientist & Director Advanced Analytics, SAP

In my previous Predictive blog, I introduced four main considerations that organizations need to keep in mind when they’re beginning that journey. Today, I’ll cover them in more detail.

1. How Do We Measure Business Value and Return on Investment?

An advanced analytics solution must make a measureable impact. If not, the solution doesn’t get noticed, never mind appreciated. This holds even more true, if the return on investment (ROI) can’t be realized as a significant opportunity to drive business growth or new market opportunities.

Take the example of a marketing campaign. The ROI is in having the intelligence to target the customers who are likely (if persuaded) to buy your product rather than finding customers who would have bought the product without any marketing required.

An advanced analytics solution will be short-lived if it creates a “wow” effect, but nothing else.  The solution must generate recurrent value, revenue, and business opportunities.

2. How Do We Use Advanced Analytics Effectively?

For your business, good questions to ask at the start of the journey are:

  • Is the enterprise truly digital?
  • Is there a single source of truth of all the data that is generated/captured by various functions of the enterprise?

These questions are important considerations. Why? Because businesses often approach advanced analytics in an ineffective manner.

Remember, advanced analytics drive value to every business function, be it marketing, finance, human resources, and so on. However, enterprise functions want often to embed advanced analytics into their business workflow and embark on advanced analytics initiatives in silos. Though there is value in doing so, the results can be underwhelming.

This is because they’re using adoptions of various technologies, methodologies, practices to address the use cases that might exists— but without an enterprise-wide vision for advanced analytics. Therefore, walls rather than bridges are built between the various functions.

The problem becomes self-perpetuating. With increasing adoption of advanced analytics solutions in various business units, the business as a whole finds it difficult to consolidate all the activities into a central initiative and have proper discipline and governance.

The solution is to create the vision and execute it across all functions— even if the pilot starts from one or two activities. The functions must agree that advanced analytics is an enterprise-wide mission. Leadership must demonstrate belief in an analytics-driven business that it is going to provide competitive advantage. In this way, advanced analytics becomes a true company asset.

3. Is Advanced Analytics Just Another Technology Project?

Advanced Analytics is not just another technology project. If considered to be a technology project, the business understands only the technical feasibility and not its business impact.

As mentioned, an advanced analytics initiative is the means by which a business gains a competitive advantage. It follows that outcomes provide the data to help make well-informed decisions.

A lesser or confined approach is a step in the wrong direction. There is no ROI associated with technology-only thinking, because no tangible results are expected as an outcome. An initiative to embrace advanced analytics must be inseparable from your business strategy.

4. Is Big Data Equal to High Quality Insight?

Big Data is not equal to high quality insight.  A traditional business approach is to think, “We’ve captured huge amounts of data, but how do we  make sense of it?” This is a wrong start.

The right approach is to start with a business question in mind. That way, you can ask if the data that you have is sufficient enough to provide the answer.

These are several pieces of the puzzle that need to be put together for one to find meaningful, actionable insights from the data. This is, after all,  the quest that we embarked on.

As we now know, advanced analytics is about business change, insight and value.

“The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data”-Sunset salvo. The American Statistician 40 (1).

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Analytics, SAP

Are you Planning to Embark on an Advanced Analytics Journey?

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by Paul Pallath, PhD, Chief Data Scientist & Director, Advanced Analytics, SAP

Businessman Analyzing Graph

Welcome to the new world!  The manner in which data is generated and captured today has come of age. Traditionally the way of generating data for the most part from B2C/B2B2C business processes, was by having interactions captured as part of transactional systems in a highly structured format. But with changing technological landscape, much has changed in how data is generated and captured.

What data supports this view?

According to the ESG Digital Archive Market Forecast, the growth in data volumes that is driven by unstructured data amounts to more than 88% as compared to structured data. What’s more, Computer World states that unstructured information may account for more than 70% to 80% of all data in organizations.

The change has come because we in the 21st Century have redefined the way business is conducted. Significant advancement in internet technology has forced the need for digital online presence for most businesses to stay relevant. Likewise, every interaction that a customer has in the digital online ecosystem leaves behind a digital foot print containing huge amount of information.

Social media presences, for individuals and businesses, have increased the speed at which information travels. This has made it possible to share opinions as blogs or multimedia content. The result is the constant generation of large amounts of unstructured data.

All that Unstructured Data Is Good News for Data Scientists

However, this is good news for data scientists.

The previous figures imply that we have now Yottabytes [1024] of data at our disposal for deriving business value—and that amount of data is about to increase.

The Internet of Things with its emphasis on completely connected systems has resulted in the availability of high speed streaming data. This makes it possible for new innovations that use data to build technologies to enable machines talk to one another (and perhaps eventually become intelligent enough to remove humans from the loop)! Taking the trend into consideration, Brontobytes [1027] of data to work with will soon be a reality for data scientists.

So, what is the best way for a business to capture and benefit from this information? Of course, capturing the massive swathes of data available is an important part of the Big Data story. But it’s not the most important part.

The most vital activity is to generate insights that add value to your business. This takes vision, it takes change, it takes…advanced analytics.

For organizations embarking on a journey into advanced analytics, it’s vital to keep in mind these important considerations:

  • How Do We Measure Business Value and Return on Investment?
  • How Do We Use Advanced Analytics Effectively?
  • Is Advanced Analytics Just Another Technology Project?
  • Is Big Data Equal to High Quality Insight?

In future blogs, I’ll discuss each one of these considerations in more detail.

Let me know what you think. Did I leave one off the list?

Amick Brown would sincerely like to Thank Dr, Pallath for his contribution today .