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  • admin 9:51 am on March 30, 2017 Permalink
    Tags: , Albertsons, , Improving, Safeway   

    Albertsons Safeway and Alation Improving the Way You Improve 

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  • admin 9:47 am on September 27, 2015 Permalink
    Tags: , Churn, Improving, , , Techniques   

    Analytic Techniques for Improving Loyalty and Reducing Churn 

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  • admin 9:50 am on August 22, 2015 Permalink
    Tags: , , , Improving, , Plans,   

    Improving Financial Management Risk and Compliance for Health Plans 

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  • admin 9:51 am on August 14, 2015 Permalink
    Tags: , , , Improving, Personalisation,   

    Big Data: Improving Customer Experience Through Personalisation 

    Retail is a market which has been growing exponentially in the past few months. Reports suggest that the world retail market will grow by 5.5% to reach US $ 23.8 trillion in 2018. As the number of retailers increase and social media starts picking up considerable vogue in the marketplace, the need for involvement of analytics in retail has increased manifold. Big Data has answered the call effectively with its implementation across many retail outlets in the world.

    On the other hand, many Indian retailers have been hiding from the forefront of analytical technology for a very long time. Reputed large retail brands have been ignorant towards using this expertise to their advantage. Therefore, customer complaints about the unavailability of certain products are frequent in this scenario.

    This has affected labor productivity in Indian retail. According to a McKinsey study conducted in 2010, the labor productivity in India is only 6% of that in the United States. The perfect solution to this problem lies in applying Big Data solutions to the marketplace.

    For example, if a retail store has a certain product which is rapidly selling out, there arises a need for its demand to be kept in check for avoiding lost revenue and profitability. Mostly, retailers believe in word-of-mouth marketing to propagate their business. But, inaccuracies due to perceptual differences come hand-in-hand with this method, which leads to the business faltering at some ends. Rectifying this, Big Data can set up predictive trends about these products, combining enterprise data with other relevant information, which include social media patterns, web-browsing patterns and TRP’s in advertising.

    Another scenario where Big Data can make its presence known is in cities where a certain product is the leader in the market, catering to the USP of the city in which it is located. For example, if a city is known for its student population, the swiftly-selling products in the market will include ready-to-eat food items. Some brands fail to recognise these regional trends and, as a result, lose out on potential opportunities in the market. Incorporation of Big Data would help in such circumstances, as it would identify customers according to their expected buying behavior. Also, financial crunch is a factor which is starkly different in every city, playing a major part in analysing customers regionally.

    On the whole, Big Data has reached impenetrable heights in many areas. But, the application of this proficiency in Indiais still a question mark, rapidly proving to be one etched in indelible ink. But with the right awareness and application, an intense hope can be lit in the minds of retailers about a better future in this business.

    Sunil Jose is Managing Director at Teradata India. He joined Teradata in June 2014, bringing with him more than 25 years of technology industry leadership experience that encompasses enterprise software and hardware knowledge, general management, sales & marketing , strategy development and executive management experience.

    The post Big Data: Improving Customer Experience Through Personalisation appeared first on International Blog.

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  • admin 9:53 am on June 5, 2015 Permalink
    Tags: , , Improving, , , , , Quiz,   

    How Close You Are To Leveraging Individualized Insights And Improving Interactions With Customers? Take The Quiz! 

    quizData-driven marketing is the strategy of collecting and connecting large amounts of online data with traditional offline data, rapidly analyzing and gaining cross-channel insights about customers, and then bringing those insights to market via interactions tailored to the customer, at their point of need and in real-time. It enables highly individualized insights, which can help you develop collaborative, enduring bonds with customers.

    Whenever I recite that definition, I see marketers’ eyes light up. They’re instantly eager and ready to jump right in. But remember: Data-driven marketing strategy is not a one-size-fits-all solution, and you can’t implement a data-driven approach overnight. Instead, you’ll need to proceed methodically, developing individualized insights through a systematic framework of tools, standards, and practices implemented to integrate, automate and improve your current processes.

    Do you have questions about where your organization currently stands and how far you need to go to start realizing the benefits of individualized insights? If so, please take the time to check out our new set of assessment tools designed specifically for marketers like you.

    Within a few minutes, these quick assessment tools will help you determine how well your marketing processes and programs stack up. All you’ll need to do is rate your organization’s data-driven maturity from 1 to 5 in a few different functional areas (1 = infancy; 5 = fully optimized), then add up your scores and evaluate. 

    The four self-assessments cover the areas of data system integration, marketing analytics, digital marketing and marketing resource management:

    Data System Integration

    To develop a strong data driven marketing strategy, you’ll need to integrate disparate databases of customer information. Effective integration is critical because it lays the foundation for discovery of individualized insights through use of data and analytics. But it may be difficult to gauge the effectiveness of your integrations. How do you even know if you’re on the right track? This self-assessment will help you better understand how your data system integration stacks up. 

    Marketing Analytics

    Marketing analytics shed light on effective methods for engaging customers and help you leverage individualized insights to create interaction strategies that drive more revenue. But do your analytic tools let you see every data point that can add to an understanding of customer behavior? Use this marketing analytics self-assessment to gauge where you stand.

    Digital Marketing

    Today’s customers engage in a variety of digital spaces—email, mobile, social, websites, etc.—and you have to be sure you’re delivering the right message across all of these channels and platforms. Are you confident in the effectiveness of your digital execution? Take this digital marketing self-assessment  to determine if you’re on the right track.

    Marketing Resource Management

    Your marketing team needs to act on process and program insights to optimize the impact of its initiatives. Done right, marketing resource management enables more agile marketing that quickly responds to individualized insights. But controlling processes and programs can be challenging. This marketing resource management self-assessment will provide insights to help you improve your data-driven strategy from the ground up.

    After completing these four self-assessments, you’ll better understand where you need to improve so that your data-driven marketing strategy can empower your organization with individualized insights.

    And here’s the best news of all: No matter where you are currently, Teradata can help you go further.

    The road to individualized marketing that actually drives revenue is built by the increased data flexibility made possible by operational efficiency and paved by real-time inbound and outbound messaging enabled by individualized insights. Learn more about how to power your marketing by downloading our new whitepaper, Essential Steps to Marketing With Individualized Insights.

    The post How Close You Are To Leveraging Individualized Insights And Improving Interactions With Customers? Take The Quiz! appeared first on Teradata Applications.

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  • admin 9:49 am on May 15, 2015 Permalink
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    BlueCross BlueShield Tennessee Improving Customers Lives With Individualized Insights 

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  • admin 9:54 am on February 5, 2015 Permalink
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    4 Tips for Improving Customer Satisfaction with Data Analytics 

    Customer Experience Management (CEM) is a major talking point in a number of industries, including Telecommunications, Financial Services, Retail and even the Public Sector. While there is no homogeneous definition and processes associated with CEM, the industries seem to understand what CEM is meant to do for them, namely, drive a greater level of customer-focus / customer satisfaction; generate new revenue streams; and help maximise profits.

    Here are some tips for improving customers’ experience and how analytics will help in maximising customer satisfaction and market share.

    1. Product or Service

    This may seem obvious on the surface but requires a good understanding of the differences that will help in managing customer expectations. Gone are the days when the only thing that mattered was the ‘3Ps’ (Product, Price and Place) when it comes to growing market share. There are many industries that don’t have physical products or inventories. For many Financial and Telecom service providers, ‘Service’ is their product. This allows for greater flexibility and agility for creating service products at different price points that will appeal to the target market segment.

    This is in contrast to products (i.e. consumer equipment) that requires upfront capital expenditure for production as well as significant operating expenditure for the sales distribution network and inventory. Customer satisfaction of using consumer equipment is inherent in its engineering design quality and reliability whereas for service products it arises from the reliability of the infrastructure that delivers the service.

    It could be frustrating if the set top box fails to deliver the premier sports show that you may have been waiting for! What if the ATM is out-of-order when you needed the cash? You are most likely to be frustrated with your mobile service provider if you are unable to make that emergency call after several repeat attempts!

    Path Analysis is a good tool to predict failures of consumer premises equipment and/or infrastructures before they arise and helps to proactively manage customer expectations. Here is an example from the telecom network performance. Path Analysis is also good for predicting ‘path to purchase’ and ‘path to out of stock situations’ during customer acquisition stage of customer life cycle management.


    2. Product Development

    Creation of ‘service product’ at competitive pricing is relatively easy compared with manufacturing of consumer premises equipment which requires breakeven points to be profitable. However, many organisations create service products that are ‘one size fits all’.

    Mortgage financing and mobile price plans are examples of this type of ‘inside out thinking’ in product development. Consider a customer with $ 70 mobile plan that gives her 700 minutes of talk-time, 3GB of data and 4000 SMS per month. If she only uses 200 minutes and 1 GB per month then she is overpaying the service provider – likely not a very happy customer. Why not develop a personalised price plan that fits the individual customer’s life style?

    This type of ‘outside in thinking’ requires discovery analytics to understand customer’s buying decision / behaviour to tailor a product that is aligned with her / his life style. Every telecom service provider has the detailed data of their customers’ service usage which they can use to simulate various tariff plans that provides the best margin while helping the customer save. This is their ultimate weapon that their competitors don’t have! Can there be better way for agility in customer retention?

    Social network analysis can provide clues about a customer’s calling circle and sphere of influence. When combined with Affinity analysis it will provide strong indications of the propensity for the customer to take up a product / service that fits the customer’s needs.

    3. Customer Service

    When it comes to Customer Service there is no inventory to keep or product catalogue to maintain, but its success solely relies on the skills of well trained staff / partner network who can deliver quality service. In other words, quality of experience (or lack of it!) is realised at the time at which the customer service is delivered – every single time. Paying attention to this subtle difference in ‘service’ delivery and managing customer expectation is the key to keeping a satisfied customer.

    Proactive analysis of customers’ sentiment about new product launches and/or issues with a current product or service could be analysed from social media well ahead of a customer’s intention to contact the Call Centre. Discovery analytics performed using Text Analytics and/or Sentiment Analysis functions on Call Centre contact notes and social media data will enable new insights to be gained about competitors as well as own products/service as perceived in the market. A well trained Customer Service staff can use the insights gained from discovery analytics to help improve customer satisfaction.


    4. Channel Management

    Cutting costs of channel by reducing retail outlets often leads to creation of low cost channels such as telesales and online without considerations for the customer’s preference. Significant number of customers are not willing to accept offers on telesales channels.

    Response rates of online channels can also be generally low leading to ineffectiveness of these channels. Geospatial analytics overcome these limitations to spot customers who frequently visit retail stores and those who don’t. Identifying stores that are closer to where customers live provides the opportunity to find stores that are good at selling particular offer and / or good at resolving problems. Those customers who visited your online channel can also be directed to a close by store to bridge the online-offline gap.

    Is your organisation well positioned for the next generation of discovery analytics competency?

    Sundara Raman is a Senior Communications Industry Consultant at Teradata. He has 30 years of experience in the telecommunications industry that spans fixed line, mobile, broadband and Pay TV sectors. He specialises in Business Value Consulting, business intelligence, Big Data and Customer Experience Management solutions for communication service providers. Connect with Sundara on Linkedin.

    The post 4 Tips for Improving Customer Satisfaction with Data Analytics appeared first on International Blog.

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  • admin 9:46 am on October 29, 2014 Permalink
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    Teradata Shows How Improving Integration Can Lead to Better Business Alignment 

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