Tag: Customer Retention

Customer Analytics Solutions Help Retailers to Improve Sales and Customer Retention

Quantzig’s recent study on customer analytics for a leading retailer in the US guarantees 15% decrease in customer churn rate.

Retail management through customer analytics

The best decisions made by any retail brands often rely on customer analytics to understand the demands and preferences of the end-users. Digitalization of the retail industry is turning it into a data-rich environment that is growing at a phenomenal rate. Tackling major issues such as high customer churn and inventory pileups is gaining importance in the retail industry. By analyzing historical data such as customer data, sales data, product data, transaction data, customer feedback, pricing data, promotions, and social media metrics, suppliers will gain in-depth knowledge about the demand-supply market. Expanding customer base, improving customer satisfaction, and meeting the ever-changing demands of customers is important for retailers to remain competitive in the global market. The customer analytics team at Quantzig analyzes various CRM, POS, product, and other internal data to endorse products to the customer that best fit their profile based on their interests and purchase history. The study also offers improvement in the product bundles and price modifications based on customer preferences.

By leveraging technology, retailers are improving client interactions and increasing consumer satisfaction levels. The implementation of IoT will help companies to access data to personalize customer experience, provide improves user interface that increases customer experience, and makes devices more secure. Other advanced technologies launched to improve consumer experiences include chatbots, voice search engines, and messaging support systems.

Emergence of  AI (artificial intelligence) and virtual assistance

The introduction of AI and virtual assistance is a game changer in the retail industry. These systems interact with customers and perform smart algorithms to match the requirement and offer the products in accordance with their preferences. Moreover, these systems offer additional functions to retailers by analyzing the sales data to improve promotional strategies, inventory management, and optimizes the supply chain. The systems are designed to provide accurate demand and supply forecasting to improve logistics management and reduce the cost of operations.

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Mobile pay systems

Mobile and app-based payment are gaining popularity in the retail industry. It is estimated that 70% of the mobile users in the US will move to mobile payment by the end of 2017. By implementing this modern technology, retailers will ensure sales targets are met and offer convenience to end-users to select from a varied payment option. The introduction of mobile POS systems, custom mobile payment apps (Kohl’s Pay), and third-party options such as Apple Pay and Paytm will revolutionize the retail industry.

Outcomes and solutions offered

Quantzig’s expert team on customer analytics develop next best action and offer analytics solutions to improve sales and customer retention to a leading retailer in the US. Some of the solutions offered are as follows:

  • Identified the right campaign or channel for each customer stage based on the association between marketing response and marketing efforts
  • Provided matrix and analysis for customer footfall by weekend and weekday
  • Increased the marketing response by 2-fold due to the implementation of targeted marketing strategy
  • Focused on the proclivity of a customer to respond to unique marketing activities and the likelihood of a customer to purchase products
  • Offered descriptive insights into customer demographics such as income group, marketing response index, age segment, and promotion usage

The complete case study on customer analytics which helps decrease customer churn by 15% for a leading retailer is now available.

Recent case studies that might interest you

For any queries, reach us at – hello@quantzig.com

Customer Experience Analytics Powers the Next Generation Customer Engagement Strategies

Typical Customer: ‘I don’t think I like this’

Typical business: ‘Sorry, but that’s all that we got right now’

And the customer was never heard from ever again.

That’s all it takes in this age of retail abundance and social media to shoo away a potential customer and have the disgruntled buyer lambast your business through clever tweets and long winding social posts. Retaining a customer, with stiff competition biting at your heels, is more important than ever, both from the perspective of your business’s bottom-line, and to avoid the aforementioned negative cascade effect. Easier said than done, right?

Enter, the insightful discipline of Customer Experience Analytics – a smart and quantifiable system of collecting, analyzing and acting upon insights that are derived from real world interactions with customers, both loyal and in the pipeline. Practically, deployment of this system will require sophisticated tracking implements, a team of expert data miners and the latest machine learning capabilities- tools that may not be readily available or easily assembled in a process exclusive work infrastructure. However, there is no denying the severely adverse impact of ignoring the discipline altogether- at the stake are the concepts of customer engagement, and profitability that is directly linked to customer loyalty.

A Simple Plan- Know Thy Customer

Customer experience analytics may seem daunting to a business that hasn’t already experimented with the varied customer engagement initiatives that are cumulatively bundled as customer retention solutions. On paper, the process flow is simple enough.

  • Asking the customers, the right questions (through such mediums as surveys, social media, or as part of the backend call center interactions). Remember, data has a habit of piling up, quickly.
  • Processing the massive pile of data to derive actionable insights. You will need a data scientist or two to make sense of this heap of structured and unstructured data.
  • Actions that are motivated from the aforementioned insights must be tested across geographies, demographics and/or time. What worked yesterday may not necessarily work today, or may need simple/expansive modifications to improve the inherent efficiency.

As a business, the most profitable option for you is to key in a system that needs minimal management, is highly scalable and accounts for the whole spectrum of fixed and variable contributing factors.

BIG DATA and Analytics with Quantzig

As the evolution of technology has skyrocketed, the platforms for the interaction between the business and its target audience has doubled up too. The prodigious depth of data that is thus generated, both qualitatively and quantitatively, holds the key to understanding customer behavior and developing business strategies that are correspondingly effective. Insights derived from a single source (say a storefront or the business’s social media page) can be very limiting and misleading. BIG DATA on the other hand, collates information from multiple sources, thereby the resulting insights are stronger and likely to perform under any test condition.

At Quantzig, customer experience analytics is one of our primary specialties. Aided by an experienced team of analysts and the most cutting edge business intelligence and visualization tools, your big data will be expertly analyzed for the tell-tale signs that will help you keep the footfalls and mouse clicks coming. Talk to Us.

Finally, revisiting an older story…

Typical Customer: ‘I don’t think I like this’

Enlightened business: ‘Sorry, but here- the same piece in dark blue, and if you would let us, your item shall be hand delivered to your home by 9am tomorrow, before you head off to work’

And the customer never had a reason to seek out another storefront again.

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Customer-Centric Merchandising Leads to Increased Customer Retention

Consumers today are highly connected and informed, and can easily convey their preference, demands, and dislikes to the world at large via the Internet. To effectively retain customers and cater to their needs, businesses should utilize customer-centric merchandising.

Customer-centric merchandising rethinks the entire merchandising process, using analytics to determine consumer patterns and then focusing on the people who buy the product rather than the product itself. In customer-centric merchandising, management and marketing decisions are made on the basis of customer preferences and buying habits. This customer focus allows retailers to stay one step ahead of their competition by responding directly to proven customer buying patterns and preferences, improving the customer experience and leading to increased customer retention and satisfaction.


How can you determine what the customer wants?

Customer preferences can be determined through a wide variety of means, including sentiment analysis, the use of advanced analytics services, analysis of social data, and customer survey questions and reports. Due to the wide availability and huge amount of information about customer habits, likes, and dislikes available on social media, retailers currently face very few roadblocks when trying to determine how best to cater to consumers in a particular demographic or market.

With data so easily accessible, retailers just need to choose the right customer analytics solutions, marketing analytics solutions, and customer retention strategies to properly and fully benefit from this wealth of information. Retailers need to identify the largest and most lucrative opportunities presented to them, taking into consideration their resources, budgets, and the typical demographic breakdown of their current customer base.


Catering to customers

Once customer-related insights have been derived and opportunities have been identified, the next step is putting them to use and creating marketing and retailing strategies. Retailers should implement strategies that reward loyal customers and increase long-term retention, as well as those that simultaneously target both new and existing customers.

Retailers should use the information they have collected about customers to establish customer-centric price and promotion plans. Integrating customer focus into price plans will ensure that their products are affordable for the majority of the consumers they wish to target, and should take into account the average consumer’s income and economic standing as well as other factors like inflation. Customer-centric promotion plans should take into account how different customer segments react to different types of advertising and promotion methods. Millennials, for example, respond positively to online and digital marketing, including social media campaigns, while it’s generally less effective to target Baby Boomers through these means. Promotional plans should also eliminate ineffective promotions and prioritize promotions that offer popular items or target the retailer’s largest and most profitable consumer group.

A customer-centric merchandising approach also affects the stock that a retailer has on hand. They can determine what to keep on the shelves and what to get rid of by taking into account what consumers are buying and what they would like to buy should it become available to them.

Putting the customers first can be the key to success for retailers if they utilize the data that’s available to them properly, and if they take advantage of advanced analytics services and tools to derive actionable insights from that data. Customers are making their wants and needs loud and clear to retailers—now it’s time to act on that information and seize its potential.

How to Harness the True Value of Social Data

Social and digital media have revolutionized the way that companies can get feedback and information on customer preferences, habits, and opinions. There’s a huge amount of data out there on what people want and what they like, with more and more posts being generated daily: on Twitter alone, there are more than 6,000 posts made every second (that’s around 200 billion posts per year!). To utilize social data successfully, companies need to cut through the billions of social media posts made every day and identify customer insights that are most important to ensuring their long-term success, customer retention, and customer satisfaction. To truly unlock the power of social data, there are five main steps that you should follow:

  1. Identify the social media platforms that you want to collect data from. Large, general platforms like Facebook, Twitter, and Instagram should be included for most companies, while more niche or focused platforms, such as Pinterest, may not be worth gathering data from for everyone. Companies should have a thorough understanding of social media and their consumer base to identify where the majority of discussion and promotion happens. A healthcare equipment company, for example, would likely get their best results by sticking to large platforms and excluding niche platforms like Pinterest and less widely used platforms like Myspace and Peach.


  1. Define terms related to your product or brand that you want to look for in the social data that you’ve collected. You can then use social listening tools and other advanced analytics services to find posts containing these words and phrases. For example, a company may look for a product name together with tone- or mood-indicating words like “want,” “bad,” and “like.” Sentiment analysis can also be helpful during this step.
  2. Categorize the data you’ve found by topic, platform, and brand. This can be done manually, but it is more efficient and faster to input the data into a database. Categorizing and organizing the social data you have collected will make the process of analysis easier and will allow you to analyze posts from different platforms in different ways.
  3. Analyze the data you’ve found and the relevant posts that you have targeted and collected using analytics tools and marketing analytics solutions to produce actionable insights. Social data analysis and social media analytics give companies a comprehensive understanding about the consumers they are trying to reach. The insights gained from analyzing social data will tell you what your consumers think about specific products, marketing strategies, and brands, and will allow you to form decisions about how to cater to their needs and opinions. It will also allow you to identify patterns and predict future outcomes.
  4. Form strategies based on the actionable insights that social data analysis has provided you with. These strategies should effectively address consumer concerns, preferences, and issues that you have found in your social data analysis, and should aim to increase sales, consumer retention, consumer satisfaction, and enhance the probability of your business’s long-term success.

Social media is becoming more and more crucial for reaching consumers, marketing to them, and understanding their habits and patterns. Social data gives companies a huge opportunity to cater to and attract consumers, but many companies aren’t using it right or are underestimating the value that collecting and analyzing social data can have. These four steps are essential for social data and social media analysis and should be combined with knowledgeable analytics departments and employees to have the greatest effect possible.

Churn prediction and customer retention analytics delivers 85% reduction in customer churn for multinational bank

Business Challenge: Reducing customer churn and improving customer retention

A leading multinational private bank wanted to understand the cause for high churn from its corporate clientele in the UK market, and improve customer retention.

Situation: High customer attrition within few months of partnering

The client was facing high churn with its corporate accounts. The clients were applying for cancellation of accounts within a few months of partnering with the bank. Due the high cost of customer acquisition, the bank was incurring considerable losses. The client wanted to decrease attrition and improve customer retention, in order to generate profits.

Solution/Approach: Retention and churn modeling on the customer transaction and behavior data

We used retention and churn modeling on the customer transaction and behavior data, in order to identify patterns in customer attrition, and discern the causes for customer defection. We also used predictive analytics for churn prediction to identify clients most likely to cancel partnerships, and suggested remedial actions.

Impact: 85% reduction in attrition and 12% improvement in ROI

The client was able to identify the accounts with highest profit potential, and most likely to defect. Client developed targeted customer retention strategies which improved the overall customer experience, and was able to reduce attrition by 85%, and increase ROI by 12%.

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