To utilise customer information in as many of their business activities as possible, should analyze the timely and relevant data and knowledge about customer preferences, to make informed marketing decisions. Our aim is to deliver much greater value for the customer insights and to provide a Single Customer View of data by ensuring that they get targeted the most potential to be profitable through the right channels.

Key Metrics

• Understand customer trends across key focus areas such as sales, balances, and engagement
• Utilize sophisticated predictive models enhanced with Big Data that utilize the customer web behavior for analysis
• Optimize campaigns with metrics including responses, opt-outs, and customer distribution across target segments
• Monitoring the direct marketing activity campaign profitability across customer segments and channels with campaign performance tracking through the development of a customer strategy.
• Ensure targeted marketing with pre-built cross-sell/up-sell scores along with channel and product propensity scores.
• Optimize investments through detailed channel analysis including bank branches, on-line, phone
• Utilize real time offer recommendation functionality based on transaction behavior

Solutions

• Proactively gain insight into the customer segmentation and strategy understanding their needs.
• Enable successful and informed marketing decisions with the ability to plan, manage, and track marketing investments
• Enhance wallet-share through better cross-sell targeting and customer engagement across key products
• Big Data ready predictive models using machine learning techniques
• Drive marketing efficiency and optimization through customized communications and real time next best offers.
• Monitor and Track Campaign Profitability

Every business would always eager to know the insights of their website analytics data for better understanding of their online demand, and the market research of customer preferences. So that the clients would increase their products, services to drive the people interested towards them. It is why the Big data can be analyzed for insights that lead to better decisions and strategic business moves by discovering the deeper insights in data lakes.

1. We enable our team to use measures on demand and domain ranks for these searches to identify gaps in online presence and know where the competition ranked in comparison.

2. Create an estimate of the impact that web activity may have on the forecast of sales. This give us the understanding of the online searches and its effects on sales.

3. Identify the most frequent sequence of pages visited by a customer and built a heat map of page sequences to identify a customer’s most likely next/exit page.

Spend analysis tools, although not new, can help procurement teams work more effectively. Every procurement team knows about these tools and uses them to some extent to capture a certain degree of cost savings. But even companies that claim they are taking advantage of spend analysis aren’t using it to its fullest extent, which is not only unfortunate but is actually putting their companies at risk.

The effective use of spend analysis can have a significant impact on a company’s profitability and operating margins by enabling intelligent planning, forecasting, budgeting, and risk mitigation.

Advantages along with cost savings

• Advance overall data management and quality

  When companies opt for spend analysis solutions, they have a more effective way to collect, store, and manage the enormous amount of data they have from all their various sources. They will integrate data from ERP and other financial systems into one centralized location, which helps close the gaps between disparate enterprise systems, especially when they are located all across the globe. When data is converged as a single source of truth, the procurement staff has quick and easy access to it, allowing them to acquire a better understanding of current and historical spending habits, trends, and patterns. It helps them gain deep, insightful intelligence into the how, where, why, and with whom of future spend.

• Enhance supplier management

  Using spend analysis effectively, companies get the spend visibility they need to identify and leverage opportunities with vendors and reduce risk. For instance, they can identify duplicate vendors and consolidate and optimize the number they work with by determining which vendor opportunities are the most valuable and cost effective. Spend visibility also helps control spending related to non-approved suppliers. Additionally, companies gain the ability to align with suppliers that encourage diversity in their organizations. Spend analysis can also identify companies that have same or varying payment terms and can encourage suppliers to transact electronically.

• Improve product categorization

  Once there is a single source of truth, companies can gain a higher degree of visibility into their spend, because diverse groups of products are easily identified and categorized within industry standards and customized taxonomies. For instance, it’s through this kind of advanced categorization that organizations promoting diversity can be identified. This kind of consistent and intelligent classification uncovers insights – such as spend patterns and trends – that reveal the true value of spend analysis data and allow for faster decision-making.

• Identify commodity spend trends

• Pinpoint risk associated with commodities

• Accelerate planning and forecasting, regulatory compliance, and the management of complex projects and contracts

• Facilitate internal and external process compliance with best practices and regulatory requirements

Challenge

The difference between companies that grow and those that don’t is customer retention. The more customers that you can keep and continue to sell to, the more likely you are to achieve your business goals.

Investment in customer acquisition far exceeds investment in retention. Yet, selling to an existing customer is 6-7 times cheaper. So, why are companies spending most of their budgets on generating new customers?

Solution

Standard data formats and attributes that can be populated based upon the client data. For example, to calculate a customer score for the ‘Value’ dimension, Annual spend per customer may be available, whereas Share of Wallet may not, at least initially.

The Retention Targeted Model will generate a Customer Value score based on whichever combination of Value plug-ins are activated. As data becomes available for additional plug-ins, the process does not need to change, simply the accuracy of the score is improved.

Each dimension generates a score for each customer, which is then combined to create a retention activity priority score. This score is then passed to the retention processes, which depending upon the client, may be manual or automated. The model will progressively learn as more data is introduced.

Digital and personal media will continue to grow exponentially and create new channels for customer insight, interaction and engagement. Retailing will evolve toward a digital retail environment where shoppers will have almost infinite visibility into product choice and price details. The retail industry will need to be more personal, and customer data will become a key enterprise asset. Converting digital data to customer insight will be the main criteria for market penetration.

Key things to be noted:

• Know which Items Your Customers Care About

  The more you know your customers, the better. Understand which products they value most and how these items drive your core business and shopper perceptions. Leverage data and science to identify and refine key value items (KVIs) based on your customers’ price response, price perception, revenue contribution and key business metrics.

• Identify and Respond to Your Key Competitors

  Go beyond traditional rules and competitive sets. Identify which competitors matter to your customers based on competitive and price elasticity. Leverage competitive and your own price history to analyze how shoppers respond to competitive price changes. Determine the relative importance of each competitor, and respond intelligently and strategically.

• Determine the Right Pricing Strategy

  Ensure that your pricing strategies are effective and drive your objectives. Analyze how shoppers respond to your prices and use science to determine the best pricing strategies at any level of your merchandise hierarchy. Compare and refine as an ongoing process to ensure maximum results as your business and conditions evolve.

• Gain a Detailed Analysis of Your Promotions Performance

  Understand each offer’s impact on profit, revenue and units along with other metrics important to your business. Avoid pitfalls such as promoting the wrong items or excessive discounts that fail to reach their desired goals. With in-depth insight into historical offer effectiveness based on facts and science, you’ll improve your promotional performance moving forward.

• Determine How Stores and the Online Channel Should Align

  Strategically group your stores, categories and online channel for optimal performance. By analyzing customer sales patterns, elasticity, demographics and other attributes, you’ll maximize your opportunities and align your brand, categories and selling outlets to your customer base. Stay ahead of changing demographics and patterns as they shift over time.

• Get Answers to the Tough Questions

  Take advantage of Advanced Analytics to get the answers you’ve been seeking. Powerful analytics spanning multiple areas across pricing, promotions and markdowns deliver invaluable insights and knowledge. Leverage our latest science and expertise to obtain a detailed deal analysis, key value analysis, coupon analysis, competitive response analysis, item cluster analysis, or one of the many other analyses available to help accelerate your ROI. Just ask

• We also provide:

  • Business Centric Solution Provider
  • Extensive Expertise within the Retail Industry
  • Technology Agnostic with Strong Business Partnerships
  • Developed Solutions to Accelerate Delivery and Outcomes

We provide the best practices of delivering managed services to combat rising support costs, increasing inefficiencies and higher risks and to deliver tangible results by taking a strategic, flexible, and agile approach to managing the complexity of your information management environment.

Managed Services are designed to ensure reliable service to the business, cost reduction, risk mitigation and customer service excellence.

Business Services - Improvement and minor works to support business outcomes

Support Services - 24x7 support on site or off-site

Application Services - Application Monitoring, Maintenance and troubleshooting

Benefits of opting to Managed Services

• Improved performance with higher productivity

  The managed services model will free up the rest of your employees from any IT concerns. It will also scale out any processes that are not helping the company reach its goals.

• Improved service quality and reduced risk

  In a managed services model, the managed IT service provider takes all the risks. If something damages the technology in any way, the provider is the one that’s responsible to repair it. Higher revenue by sharpening focus and reorienting resources on your core business

• Reduced operating expenses

  This refers to a month-to-month payments that will never fluctuate. This way your company will know precisely how much it will need to budget for its IT.

• Knowledge Retention

  Since an outsourced vendor runs the company’s IT department, there is no employee turnover. We keep the information about your company on file. They will also bring expertise from previous clients to your company.

• Continuous improvement

Customer segmentation, also referred to as market segmentation, is defined as the process of finding highly similar sub-groups within a heterogeneous larger market. This approach was originally used in direct marketing to target and focus on well-defined market subsets.

Why Customer Lifetime Value (CLV) Segmentation?

Acquiring and retaining profitable customers is more challenging than ever in today’s competitive environment. Digital innovations and technology advancements are reducing time to market, thereby making it more difficult to differentiate products and services as well as maintain customer loyalty.

We understand customer base, and design targeted marketing campaigns to reach specific customer segments with offers that are tailored to their needs and preferences. The process of segmentation begins with observing customer actions and continues with learning about the demographic and psychographic characteristics of these customers. Segmentation analysis has as inputs customer transactional, demographic and psychographic data.

In an era of increasing personalization, businesses must learn how to microscopically target their prospects and customers. People have very little time and appetite for generic messages and unless businesses learn how to customize or personalize their messages for each and every prospect, they will have a hard time competing. Customer segmentation takes on a whole new meaning in this context. Inbound marketing experts call this process as creating a "segment of one".

Customer Lifetime Value (CLV) is one of the core foundations of modern Customer Relationship Management (CRM). It is used for supporting both strategic and tactical decisions. For example, the calculation of the CLV in the automotive industry, characterized by long purchase cycles is totally different from that of retail or what are termed fast moving consumer goods.

Benefits of Advanced Analytics Customer Lifetime Value(CLV) Segmentation

• Better identification of profitable customers
• Expanding wallet share by identifying cross-sell and upsell opportunities
• Better campaign response rates by predicting the next best product offer in an effective way
• Acquiring new profitable customers by targeted marketing campaigns
• Increased customer loyalty by providing business insight on how to offer right products to right customers at the right time
• Increased revenue with better alignment to meet the needs of high value customers
• Maximised ROI by prioritising investments on marketing activities, improvement initiatives and the development of products
• To reduce costs by delivering marketing messages executing campaigns with precision rather than spreading them like peanut butter.

Data and technology have helped businesses evolve so rapidly that in just the past year, innovative technologies and capabilities such as data science, artificial intelligence, data analytics, and Big Data processing have allowed businesses to benefit from data in ways unimaginable before.

The possibilities of technology are incredibly exciting; however, technology is always a means, never an end destination. Lead with strategic direction and be clear on what you are targeting with data-driven innovations.

The main challenge for data monetization is building a solid foundation for running a new, scalable and profitable data business. Overcome it by focusing on creating horizontally connected teams and putting customers first. Install small teams at the edge of the organization with a clear vision and strategy that aim to drive rapid business outcomes. Ensure that they’re horizontally connected to include a mix of talented outsiders and forward-thinking corporate veterans, who help keep the bonds with the core business and break down silos between core and edge teams.

Execution Strategy of Enabling Business Outcomes

• Reliable and high-quality data

  When enriched with other data sources and processed using with machine learning algorithms, the value of data increases immensely. Go for the infinite possibilities but temper with a dose of reality. Why? Not all data is created equal and being aware of bias in the data is crucial for understanding the extent of a model’s accuracy and avoiding shortcomings on algorithms and biased models.

• Transparency

  Ensure model transparency that avoids black box and that algorithms remain accurate over time, meaning the reasoning behind a decision or recommendation can be explained at any time.

• Build in circular learning loops

  Data-driven applications operate on diverse data sources, combining analytical and operational data to predict and prescribe what to do next by providing transparency and relevant insights in the form of industry benchmarks and peer-to-peer comparisons. Simulation capabilities and recommended actions based on algorithms guide the user in the decision-making process. Incorporate user-generated behavioral data and improve recommendations by correlating interactions back to the source of data to close the loop.

• Combine data and domain expertise

  This is crucial because data-driven applications solve new problems in new ways by connecting the right data in a meaningful and contextualized way. The creation of value becomes much more problem-solving focused, providing solution for industries and for horizontal business functions like human resources, sales or finance. Use your domain expertise to find what problem to solve and let the data lead to new insights and signals. The best algorithms are the ones based on contextualized domain knowledge on processes in combination with data and behavior.

We build the best automation tools that programmatically compiles, moves, packages, and prepares code for release. In this growing IT environment you face increasing pressure to deliver results with greater frequency and agility, these concerns become significant and noticeable.

Build automation helps your IT department cope with the challenges as below:

• Automate repetitive tasks around your deployment workflow such as moving files, executing scripts, and copying data
• Test deployment steps with precision and confidence in pre-production prior to final release
• Deploy and release with the push of a button
• Automatically deploy the latest release at regular intervals, or whenever the code is changed

Benefits to a company or organization with the implementation of Build Automation Tools

• Improved operational support and faster fixes
• Good processes across IT and teams, including automation
• Increased team flexibility and agility
• Happier, more engaged teams
• Cross-skilling and self-improvement
• Collaborative working
• Improves quality of software releases
• Less time on administrative tasks
• Increases reliability of deployments
• Catches build errors in advance
• Reduces number of human errors
• Rapid feedback on how code changes affect the release

Today’s data sources are plagued by redundancies and duplications, lack of consistency and standardization, and missing or incomplete information. Data integrity solutions are designed to optimize the quality of enterprise data, to ensure a consistent, timely, and accurate view from each and every interaction point.

Data integrity solutions greatly improve the completeness and accuracy of data from enterprise sources, that solve business problems and provide tangible benefits to our clients while enabling them to improve the quality and integrity of their data in a sustainable manner

Businesses or IT organizations always want to stay competitive, remain profitable, and meet evolving customer demands. Data integrity solutions can help them to overcome these challenges by ensuring the reliability, accuracy, and timeliness of critical information.

Broad-reaching capabilities ensure data is always “clean” and consistent.

Some of the extensive and broad-reaching data quality management capabilities include:

• An automated rules engine cleanses the data, triggering instant changes to existing data to eliminate mistakes
• An automated rules engine cleanses the data, triggering instant changes to existing data to eliminate mistakes
• A real-time data quality firewall can be built, complete with real-time reporting and monitoring
• Centralized management of business rules, information integrity, and data flows provides a single point of integration and management for data from external master data systems and other sources.
• Restrictions, constraints, and other data quality rules can be defined and implemented, and then automatically applied to data values across the information landscape
• Information can also be enriched and enhanced by appending it with relevant content gathered from external sources
• Match and merge functionality synchronizes information across multiple data sets to promote consistency
• Robust data governance capabilities enable end to end remediation of data quality issues
• Data can be profiled and analyzed to assess its quality and immediately identify and correct integrity issues

Benefits

• Improved business processes by detecting issues early and reducing impact
• Reduced business process errors by (potentially) identifying them before they occur
• Improved data quality and integrity in a sustainable manner and monitor to ensure continuous improvement
• Reduce support cost through better quality data and reduced incidents.

Business Transformation solutions accelerates your transformation and simplification programs by capturing and analysing insights from your existing data and information systems. Our leading discovery and analytics platform underpins the transformation to the targeted state in a more cost effective way.

Digital transformation is the profound transformation of business and organizational activities, processes, competencies and models to fully leverage the changes and opportunities of a mix of digital technologies and their accelerating impact across society in a strategic and prioritized way, with present and future shifts in mind.

While digital transformation is predominantly used in a business context, it also impacts other organizations such as governments, public sector agencies and organizations which are involved in tackling societal challenges such as pollution and aging populations by leveraging one or more of these existing and emerging technologies.

In the scope of this digital transformation overview, we mainly look at the business dimension.

The mentioned development of new competencies revolves around the capacities to be more agile, people-oriented, innovative, customer-centric, streamlined, efficient and able to induce/leverage opportunities to change the status quo and tap into new information- and service-driven revenues. Digital transformation efforts and strategies are often more urgent and present in markets with a high degree of commoditization.

Business Benefits

• Accelerated strategic transformation start-up time by 90%
• Better visibility of data and technology landscapes
• Cost optimisation & Risk mitigation
• Enhanced operational efficiency up to 95%
• Enabled Business Agility & Faster time to market

Retail Pricing Intelligence helps you optimise your pricing strategies and increase your sales and profit margins.

Our solution offering provides you with the valuable business insights by extracting and transforming data from competitors’ websites into actionable information. Our unique service collects more comprehensive data to allow better pricing decisions.

• Raise Sales

  Grow your sales up to 85% by monitoring your competitor’s pricing strategy. Find the good price point to gain customers.

• Increase Margins

  Increase profit margin by raising prices that are too low. Make strategic pricing decisions with high quality competitor pricing information.

• Oversee Market

  Have an overview of your market and products offered by your competitors. Find opportunities and adjust your product assortments.

The Benefits Of Pricing Intelligence

• Profitable insights with pricing data comparison
• Better data driven pricing and promotion decisions
• Offering the best deals to customers
• Increased revenue and profit margins through optimisation of pricing strategies