Tag Archives: ANALYTICS

Tweet-Up on #BigDataTalk: How I Met Your Customer: Data Driven Marketing In E-Commerce – Join The Conversation! #Event #Twitter #CX #CustServ #CMO

IBM

 

 

 

 

Join Greyhound Research (@Greyhound_R) and other esteemed panelists for a tweet-up on #BigDataTalk: How I Met Your Customer: Data Driven Marketing In E-Commerce.

WHEN: Tuesday, June 17, 2013. 3:00 PM (IST) onwards

WHERE: Twitter.com or your fav Twitter app, using #BigDataTalk

WHAT: Estimates predict that the Indian e-commerce industry may reach $70 billion by 2020. Couple this with the fact that over half a billion Indians are going to switch to smartphones in the next five to six years and you get a fair picture of the opportunity that lies ahead of the Indian e-commerce industry.

To thrive, retailers must commit themselves to change rapidly and substantially and find out ways to capture these Omni-channel opportunities. Retailers must explore and understand the customers, their lifestyle, whether in-store or online, listen to them and serve the right products and services anywhere, anytime. Simply put, retailers must move from ‘Performing transactions’ to ‘Building relationships’.

So, how can retailers leverage the power of Big Data Analytics to capture the emerging digital shoppers of India?

Join us for a Twitter chat on “How I met your Customer: Data driven marketing in E-commerce” where we discuss how Big Data Analytics can help businesses satisfy customers who are asking for tomorrow, today.

PLEASE REMEMBER:

You tweet with #BigDataTalk during the tweet-up so that your tweets show up to everyone participating in the tweet chat. Really, no point in missing out the action!

Goes without saying – but best when said – please take a moment and follow other fellow tweeters participating in the tweet-up — always great to grow your network with like-minded individuals.

Follow along, reply or ask questions, and enjoy! We look forward to seeing you on Twitter.

CE

Tweet-Up on ‘What’s real in real-time customer experience?’ – Join The Conversation! #Event #Media #Press #Twitter #CX #CustServ

We live in a world of instant where email may very well be considered the new snail mail. I’d be the first to admit too that I fit quite firmly in that group of customers who demand answers and demand them now. Edison Research tells us that “42 percent of customers who use social media for customer service expect to receive a response within an hour and 67 percent expect same day answers.” How do organizations keep up with customer demands and shift their marketing initiatives, customer service and sales efforts to meet the demands of customers? Where does real time fit in today’s customer experience?

In our next #CXO Twitter chat, guest Sanchit Vir Gogia (@s_v_g), chief analyst at Greyhound leads the conversation as we discuss “What’s real in real-time customer experience?” I will be leading the chat using Twitter handle @IBMbigdata and you can join easily using Tweetchat, where the hashtag #CXO is automatically appended to each tweet you send during the chat, streamlining the chat process.

Below are the questions we’ll be discussing as well as reference articles to help inspire the March 17th #CXO Twitter chat at 12 noon EST. Join us!

#CXO chat discussion questions

  1. What is the difference between real time and customer time?
  2. Does real time always mean the right time?
  3. How can organizations get customer time right?
  4. With customers defining real time, how should companies manage the experience?
  5. Can real-time decisions be trusted? Why or why not?
  6. Many organizations say “I don’t need real time”; is this true? Explain.
  7. How is real-time analytics different fromdecision management?
  8. How do businesses succeed at real-time analytics without breaking the bank?

#CXO chat reference articles:

#CXO Chat Guest:

Sanchit.jpg Sanchit Vir Gogia (@s_v_g) is the chief analyst and CEO of Greyhound Research, an independent IT and telecom research and advisory firm. He also serves as Founder and CEO of Greyhound Knowledge Group that operates under four brands: Greyhound Research, Greyhound Sculpt, Greyhound Technocrat and Greyhound Neo.Sanchit is a highly recognized and reputed IT analyst, consultant and advisor. He is also the author of the famous blog, As Disruptive As IT Getsthat has readership from over 100 countries. Sanchit’s blog has been rated as one of the 50 Must-Read IT Blogs of 2013 across the globe!

What is #CXO chat?

#CXO chat is a weekly conversation every Monday at 12 Noon EST/5 p.m. GMT, on Twitter. Each week we discuss a different customer experience optimization topic.

How do you join in?

If you use a Twitter client like Tweetdeck, HootSuite or Seesmic Desktop, create a search column for the term/hashtag “#CXO” and then, as we tweet with the #CXO hashtag, all tweets tagged with “#CXO” will show up in your column. You can also follow with Tweetchat and it automatically adds the #CXO hashtag.

How do you participate?

Just jump right in! Review the discussion questions posted to prepare your thoughts and answers. When the question is posed, begin your response with A1: for question 1, A2: for question 2, and so on. No answer is wrong! We look forward to seeing you at the #CXO water cooler hosted by @IBMBigData.

Follow the hashtag #CXO throughout the week for articles, facts and nuggets on customer experience optimization. You can also continue the discussion on LinkedIn in the Customer eXperience Optimization group on LinkedIn.

Source: IBM BigData Hub

#CXO Chat Aug 19th, Noon EST: From Transactions to Contextual Engagement: Strategy Please? with Sanchit Vir Gogia, CEO of GKG #Event #Media #Press #CXO #Chat #Twitter

“Competitive differentiation depends on pervasive customer engagement in a business environment that is proactive, innovative, agile and people-centric. Using Tom Peters’ principles such as “bias for action,” every person in your organization should be empowered to deliver maximum value to the customer at every moment. Where big data is concerned, experience optimization, next best action, stream computing and self-service contextual analytics can be key components in an action-biased culture that delivers continuous customer satisfaction.” [Adapted from Big Data As a Strategic Asset: Got Guru?]

In our next twitterchat guest, Sanchit Vir Gogia, Founder & Group CEO, Greyhound Knowledge Group, joins us as we discuss “From Transactions to Contextual Engagement: Strategy Please?” James Kobielus, IBM’s Big Data Evangelist and resident SME for #CXO chat also joins the conversation! Here are the questions we’ll be discussing as well as reference articles to help inspire the August 19th discussion at 12 PM EST.

#CXO Chat Discussion Questions:

1.    How do you build a business case around contextual engagement to get buy-in from the leadership team?

2.    How can companies plan for and cultivate exceptional pre and post transaction customer conversations and engagement strategies?

3.    How do you bridge the gap between customer value creation and value consumption?

4.    Despite the large amounts of customer data today how do businesses remain agile and shift with constantly changing consumer behavior?

5.    What should the IT team do to play a more proactive role in improving customer engagement in the near future?

6.    How can businesses use emerging technologies like Cloud, Mobility, Big Data and Social to improve customer engagement?

7.    What’s the key to being contextually relevant at any point in the customer journey?

8.    What would a customer engagement strategy for the 2020 customer look like?

9.    Is big data improving or diminishing customer engagement?

#CXO Chat Reference Articles:

The new digital customer journey: Cross-channel, mobile, social, self-service, and engaged | http://bit.ly/16fND5R

IBM Improving the Science to Apply Business Analytics for Better Customer Engagementhttp://bit.ly/13oXUhU

The Big Deal About Big Data for Customer Engagement http://bit.ly/1dcYZLw

Is Big Data Shrinking Customer Engagement? | http://bit.ly/12adprj

Big Data As a Strategic Asset: Got Guru? | http://bit.ly/1dbUUav

#CXO Guest Bio:

Sanchit is the Founder & CEO of Greyhound Knowledge Group that operates under three brands in emerging markets – Greyhound Research, Greyhound Sculpt and Greyhound Technocrat Search. The group currently employs experts with experience in IT Research & Advisory, Consumer Research and Executive Search.

Sanchit is a highly recognized and reputed IT analyst, consultant and advisor. He is also the author of the famous blog, “As Disruptive As IT Gets”. Known for his passion for emerging markets and technologies, he has gained repute in the technology community by authoring numerous thought provoking reports on topics like Cloud Computing, Big Data and Customer Engagement. With extensive experience in research, strategy, sales and marketing, Sanchit has solid experience as an IT analyst, advisor and consultant advising both end-users and vendors.

What is #CXO chat?

#CXO chat is a weekly conversation every Monday at 12 Noon EST, on Twitter.  Each week we discuss a different customer experience optimization topic.

How do you join in?

If you use a Twitter client like Tweetdeck, HootSuite or Seesmic Desktop, create a search column for the term ‘#CXO’.  Then as we tweet with the #CXO hashtag, they will show up in your column.  Or you can follow with Twubs  – http://twubs.com/cxo and it automatically adds the #CXO hashtag

How do you participate?

Just jump right in! Review the discussion questions posted so you can prepare your thoughts and answers. When the question is posed begin your response with A1: for question 1 and A2: for question 2 etc.  No answer is wrong! We look forward to seeing you at the #CXO water cooler hosted by @IBMbigdata

Follow the hashtag #CXO throughout the week for articles, facts and nuggets on customer experience optimization. You can also continue the discussion on LinkedIn in the Customer eXperience Optimization group http://www.linkedin.com/groups?mostPopular=&gid=3952442

Source: Facebook

#CXO Chat Aug 19th, Noon EST: From Transactions to Contextual Engagement: Strategy Please? with Sanchit Vir Gogia, CEO of GKG

“Competitive differentiation depends on pervasive customer engagement in a business environment that is proactive, innovative, agile and people-centric. Using Tom Peters’ principles such as “bias for action,” every person in your organization should be empowered to deliver maximum value to the customer at every moment. Where big data is concerned, experience optimization, next best action, stream computing and self-service contextual analytics can be key components in an action-biased culture that delivers continuous customer satisfaction.” [Adapted from Big Data As a Strategic Asset: Got Guru?]

In our next twitterchat guest, Sanchit Vir Gogia, Founder & Group CEO, Greyhound Knowledge Group, joins us as we discuss “From Transactions to Contextual Engagement: Strategy Please?” James Kobielus, IBM’s Big Data Evangelist and resident SME for #CXO chat also joins the conversation! Here are the questions we’ll be discussing as well as reference articles to help inspire the August 19th discussion at 12 PM EST.

#CXO Chat Discussion Questions:

1.    How do you build a business case around contextual engagement to get buy-in from the leadership team?

2.    How can companies plan for and cultivate exceptional pre and post transaction customer conversations and engagement strategies?

3.    How do you bridge the gap between customer value creation and value consumption?

4.    Despite the large amounts of customer data today how do businesses remain agile and shift with constantly changing consumer behavior?

5.    What should the IT team do to play a more proactive role in improving customer engagement in the near future?

6.    How can businesses use emerging technologies like Cloud, Mobility, Big Data and Social to improve customer engagement?

7.    What’s the key to being contextually relevant at any point in the customer journey?

8.    What would a customer engagement strategy for the 2020 customer look like?

9.    Is big data improving or diminishing customer engagement?

#CXO Chat Reference Articles:

The new digital customer journey: Cross-channel, mobile, social, self-service, and engaged | http://bit.ly/16fND5R

IBM Improving the Science to Apply Business Analytics for Better Customer Engagementhttp://bit.ly/13oXUhU

The Big Deal About Big Data for Customer Engagement http://bit.ly/1dcYZLw

Is Big Data Shrinking Customer Engagement? | http://bit.ly/12adprj

Big Data As a Strategic Asset: Got Guru? | http://bit.ly/1dbUUav

#CXO Guest Bio:

Sanchit is the Founder & CEO of Greyhound Knowledge Group that operates under three brands in emerging markets – Greyhound Research, Greyhound Sculpt and Greyhound Technocrat Search. The group currently employs experts with experience in IT Research & Advisory, Consumer Research and Executive Search.

Sanchit is a highly recognized and reputed IT analyst, consultant and advisor. He is also the author of the famous blog, “As Disruptive As IT Gets”. Known for his passion for emerging markets and technologies, he has gained repute in the technology community by authoring numerous thought provoking reports on topics like Cloud Computing, Big Data and Customer Engagement. With extensive experience in research, strategy, sales and marketing, Sanchit has solid experience as an IT analyst, advisor and consultant advising both end-users and vendors.

What is #CXO chat?

#CXO chat is a weekly conversation every Monday at 12 Noon EST, on Twitter.  Each week we discuss a different customer experience optimization topic.

How do you join in?

If you use a Twitter client like Tweetdeck, HootSuite or Seesmic Desktop, create a search column for the term ‘#CXO’.  Then as we tweet with the #CXO hashtag, they will show up in your column.  Or you can follow with Twubs  – http://twubs.com/cxo and it automatically adds the #CXO hashtag

How do you participate?

Just jump right in! Review the discussion questions posted so you can prepare your thoughts and answers. When the question is posed begin your response with A1: for question 1 and A2: for question 2 etc.  No answer is wrong! We look forward to seeing you at the #CXO water cooler hosted by @IBMbigdata

Follow the hashtag #CXO throughout the week for articles, facts and nuggets on customer experience optimization. You can also continue the discussion on LinkedIn in the Customer eXperience Optimization group http://www.linkedin.com/groups?mostPopular=&gid=3952442

Source: Facebook

podcast

Podcast: Financial Times Connected Business – Education, Education, Education #Media #Press #Podcast #FinancialTimes #BusinessTimes

In this week’s podcast: demand for quality education is growing across the world, but education itself has largely avoided automation.

Can IT improve education? And how can the IT industry work with schools and colleges to head off a growing skills shortage, especially in IT and data science?

We speak to BT’s Pat Hughes, TCS’ Satya Ramaswamy and analyst Sanchit Vir Gogia, of Greyhound Research.

Presented and produced by Stephen Pritchard.

Hear the podcast here

Source: Financial Times Podcast

Podcast: Financial Times Connected Business – Education, Education, Education #Media #Press #Podcast #FinancialTimes #TimesOfIndia #TOI

In this week’s podcast: demand for quality education is growing across the world, but education itself has largely avoided automation.

Can IT improve education? And how can the IT industry work with schools and colleges to head off a growing skills shortage, especially in IT and data science?

We speak to BT’s Pat Hughes, TCS’ Satya Ramaswamy and analyst Sanchit Vir Gogia, of Greyhound Research.

Presented and produced by Stephen Pritchard.

Hear the podcast here

Source: http://t.co/CHfstIk7nJ

Big Data – Inside In-Memory Analytics #Media #Press #ExpressComputer

When Godrej Consumer Products wanted to implement an analytics solution, it had only one focus in mind: to have overall information visibility, especially in view of the fact that the amount of data a business has to deal with is growing exponentially. Says Subrata Dey, CIO, Godrej Consumer Products, “The challenge is how to use the data to get value out of it. Our focus was on user interface, robustness of the solution and scalability. Also, there should be no deployment hassles and it should be quick to deploy.”

The organization zeroed in on Qlikview’s Business Discovery platform, which is an associative in-memory architecture and went live with the solution in 2-3 months after selection. Currently, it is being used for sales analytics and has around 500 users. However, in future it will be used for finance, marketing and supply chain management functions as well. “When organizations go for mass implementation, it is better to do it in a structural manner and eventually grow from there. The solution is very intuitive in nature, so no particular training was required and it has a lot of ad-hoc capabilities. For us, it has been a win-win situation,” he says.

In-memory analytics has been the most talked about architecture this year and the most misunderstood one. Analytics is the new building block of business decision making in a majority of progressive organizations. A recent study on “data-driven decision making” conducted by researchers at MIT and Wharton provides empirical evidence that “firms that adopt data-driven decision making have output and productivity that is 5-6% higher than the competition”. Naturally then, business analytics is a top priority for CIOs and finance executives. However, traditional analytics has its limitations that get exposed in the face of evolving trends like big data, mobile applications, and cloud computing. CIOs today, are looking for systems and tools that sift through the deluge of big data to provide fast, interactive, insightful, real time analytics.

As per a Forrester report, The Future of Customer Data Management, until recently, putting data in memory was not an option because it was prohibitively expensive compared with disk space. To support granular personalized customer experiences, in-memory data is critical to delivering faster predictive modeling, enabling real-time data access, processing big data quickly, and offering new customer insights and opportunities that used to be impossible to get. Customer data stored and processed in memory, helps create an opportunity to up-sell and cross-sell new products to a customer based on their likes, dislikes, circle of friends, buying patterns, and past orders. Key technologies that can help deliver faster insights and real-time customer experiences, include in-memory platforms and event processing platforms.

In-memory analytics is a way of executing analytical procedures. Traditional analytical engines used to conduct a lot of heavy lifting of data from the “storage” layers into the “processing” region and then again pass back the results into the storage layer for presentation by the applications. This used to create a lot of resource demand on the processors to do activities of lower criticality most of the time and had lesser bandwidth available for the real stuff which was analytics. “That whole game had been changed by the advent of in-memory analytics. Here, the processing and the data are brought closer to each other. With the development in processor speeds and also of the data I/O of RAM, the data processing is done in the RAM and not in the storage layers (hard disks). The result sets are also stored in the RAM and hence visualization and presentation is nimbler,” says Dinesh Jain, Country Manager, Teradata India Pvt Ltd.

As per Vikash Mehrotra, Sales Consulting Director – EPM/BI, Oracle India, “Speed is of essence here and this is where in-memory analytics comes into play. In contrast to traditional disk-based processing, in-memory processing makes it possible to do complex analytical computations on large sets of data in a minimal period of time.” This approach makes interacting with and querying data blazing fast—and makes real-time analytics possible. It reduces or eliminates the need for data indexing and storing pre-aggregated data in OLAP cubes or aggregate tables.

Mythical challenges?
In-memory analytics is definitely surrounded by challenges, but the real ones always seemed to be ignored. Challenges like dearth of skill-set is very often highlighted, but is it real? As per Jain of Teradata, “In-memory analytics is just a manipulation mechanism to use your hardware and infrastructure resources in a more efficient way and any in-memory optimized analytical engine is capable of doing that automatically. No new skill set is required. It may just be more of a budgeting and hardware sizing and data governance decision.”

According to Akhilesh Tuteja, Partner, KPMG, “Many times when organizations look for talent pool they only look for people who can configure systems and those with technical skills. One needs to have functional skills as well.”

Says Rajesh Shewani, Technical Sales Lead, IBM, “Lack of skills is a myth, because you do not need to train anyone on in-memory analytics, but on the specific solution. He needs to be trained on the analytics platform.”

A very important component of analytics is data visualization. Says Savita Kirpalani, Chief Analytics Officer, Rewire, “Indian organizations are not savvy about visualizations. There are so many charts but there is no skill to interpret it. How many customers can you have with such data? There has to be an appeal in the way data is presented and what you see: only then will you want to go further. Vendors need to have the ability to sell with the data that is available.” Another recurring problem seems to be around unclean data. Data needs to be synchronized properly. Especially because it is often stored on different systems in different locations. So, the challenge is how to get it together to make an implementation successful.

From the investment standpoint, organizations tend to make large investments at the outset and provide the solution only to a few back-end analysts. Also, enough business value is not attached to the implementation. As per Sanchit Vir Gogia, Chief Analyst, Founder & CEO, Greyhound Research, “CIOs should look at building a COE (Center of Excellence). This can bring IT and users together. They can redefine the testing pattern.”

According to Manish Sharma, Head of Database and Technology, SAP India, “The most critical factor is the trust in data. The reason you are taking data out is because you do not want to load the application with too many users. It is not only about speed but also what value it gives to the business process. The concept of data is a process issue and not so much to do with technology. For many customers it is a starting point to get clean data.”

Making way for in-memory
One should understand that in-memory is not a magic bullet. There are limits to how much data you can process in the RAM and hence a hybrid approach based on hot data (often used) and cold data (not so frequently used) is the most appropriate for a large enterprise. Hence organizations should have clear policies of tagging data and should have clear focus on “what” in-memory analytics is being used for.

Selecting an in-memory analytics solution is not an easy task. To begin with, in-memory architecture is divided into different segments, with different vendors offering solutions in each. Thus, there is in-memory OLAP, in-memory ROLAP, in-memory associative index, in-memory inverted index and in-memory spreadsheet. Says Gogia, “Thus, some are better at handling query, some less physical memory. Depending on the maturity of data one should select the solution. One has to see the load-time, how is the access to third party tools, interface, memory optimization. Also, what is the vendor’s approach to fit into that allotted space of memory?” Thus, organizations have to look out for product capability and how to make it work in terms of how to improvise it over time, how to maintain it and how to configure it. The decision to buy a certain solution due to an old affiliation to a vendor is a very wrong way to go about it: it can cause a huge implementation failure.

In terms of product capability, the features required are different for different organizations. Large organizations, with long term play, will have lots of needs. But smaller organizations tend to go for small solutions that are easy to implement. Says Tuteja of KPMG, “Organizations have to see how does it fit into transactional systems like ERP, CRM and how good is its visualization capability. Unlike the transactional system, where you have to use it because it is integral to the organization, with BI, one can tend to not use it. Thus, ease of use is critical.” One can start on a small scale and grow big. It could start with something as low as Rs. 40 lakh for a small tool with end-to-end implementation.

Organizations can get full value when they design applications to leverage full capability of the in-memory architecture. They should start to push calculation in the analytics layer itself because that will allow the solution to process data much faster. Sudipta K. Sen, Regional Director – South East Asia, and CEO & MD – SAS Institute India Pvt. Ltd. says, “A crucial parameter for any organization, while deciding to select a particular in-memory solution, is the ability to perform exploratory analysis on not just a sample set or subset but entire data. Another vital aspect is ‘data visualization.’ It is also pertinent that enterprises avoid data quality and integrity issues. They must manage the relationship between in-memory analytics tools and data warehouses by implementing systems and processes to ensure clean data so that queries yield quality information.”

As per Mehrotra of Oracle India, “Organizations should provide for high performance and scalable analytical sandboxes. When a problem occurs, humans can solve it through a process of exclusion. And often, when we do not know what we are looking for, enterprise IT needs to support this ‘lack of direction’ or ‘lack of clear requirement’. We need to be able to provide a flexible environment for our end users to explore and find answers.”

The Indian market
India’s digital universe is expected to grow by 50% every year through 2020. The digital bits captured or created each year are expected to grow from 127 exabytes to 2.9 zettabytes during this period. However, less than half a percent of this data is analyzed today, whereas 36% of it could provide valuable insights. This makes big data analytics and BI solutions like in-memory analytics a significant opportunity for India.

As per Jain of Teradata, “There are a lot of companies which are coming up with visualization tools focused on ‘self-discovery’ based analytics. In India, most corporations have heavily spent on traditional analytics and have stabilized them across the years. Now is a good time for them to start exploring this new mechanism of gaining maximum business value from their frequently accessed data.” However, the importance of the underlying infrastructure to support it becomes really important and an infrastructure audit before embarking on an in-memory journey is advisable.

As per Sen of SAS, “In-memory analytics uncovers lucrative opportunities not only from an enterprise standpoint but also from a state and central government perspective.” In-memory analytics is especially gaining traction because if offers the opportunity to do super-fast, real-time analytics at an affordable cost. “The growth in 64-bit operating systems and declining cost of RAM makes it possible for even small size companies in the country to deploy in-memory analytics solutions,” says Mehrotra of Oracle India.

Source: Express Computer