consumer behavior Archives

How Food and Beverage Industry Can Leverage the Power of Big Data Analytics

Big data analytics has dynamically changed the way businesses are conducted. It largely eliminates decisions based on gut-feeling and intuition by providing extensive data for driving result-oriented decision making. The food and beverage industry is no exception to this revolution due to the vast applications of big data. Big data analytics can transform the food and beverage industry right from the origin of production to the final delivery to consumers.

Food Delivery

Food consumption habits have evolved over the years with people preferring takeaways and home delivery over preparing their meals. Big data analytics can highly optimize the food delivery process by gathering data from various sources including weather, road traffic, temperature, and route. By analyzing data across all points, businesses can estimate the correct delivery time for the food along with optimizing routes to get it quicker to the consumer.

Increasing Efficiency

The use of analytics in F&B industry seems to have no bounds. Organizations can check not only the impact of market trends on global food demand but also analyze the effect of temperature on food quality. For instance, by using predictive analytics, companies in the food and beverage industry can figure out optimal inventory levels at specific locations by taking market trends and future demands into consideration.

Consumer Behavior Analysis

Retailers can use sophisticated big data analytics tools to monitor the purchase history of the consumers along with items currently in their cart to predict the next item a consumer is likely to purchase. Based on such insights, players in the food and beverage industry can create effective combos to improve their marketing efficiency.

Sentiment Analysis

Today, the customers are very sensitive with their food preferences and are more than happy to share positive feedbacks or vent out their disappointments with brands in the social media. Brands and food chains can figure out customer preferences and their emotions towards the brand by using complex big data tools such as natural language processing, social media listening, and other data analysis tools. This way, food chains and retailers can take quick action to resolve customer dissatisfaction and prevent the damage by controlling the spread of negative word.

To know more about big data analytics in food and beverage industry, predictive analytics, food delivery, and sentiment analytics:

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Four Ways to Improve Customer Experience and Engagement for Mobile Apps

There are millions of apps available for mobile platforms such as iOS, Android, Windows, and Amazon. These apps serve various functions such as entertainment, food delivery, transportation, learning, editing, shopping, communication, networking, and games. People download many such apps to serve their purpose whenever required. Recent studies suggest that an average smartphone user has around 60-90 apps installed on their phone. But the problem point for app developers is the fact that only a small minority of those apps are regularly used.

Here are some of the ways to increase the mobile app usage rate and create a unique customer experience:

#1 – Smart Notification

To improve customer experience, app developers have tried all forms of notifications, including push notifications and lock screen notifications. However, they need to be wary of the fact that too many notifications could annoy the user, and that a user may not want to visit the app every time a notification appears. Smart notifications provide a diligent solution by enabling the user to take actions right from the notification itself. For instance, news apps allow the user to read and share the content from the notification window itself. Some chat applications have made use of floating notifications to compose a reply without opening the app.

#2 – Invest in User Interface and User Experience

Many existing apps today have a bad UX/UI design; as a result of which, users get discouraged to use the apps. Even when the app is great, users can get confused with the interface and find it too complicated. Many developers outsource their UX/UI design to dedicated design companies with delightful results. A seamless design makes the user feel more comfortable and immersed in the app; thereby, increasing the mobile app usage rate.

#3 – Cross-Platform Compatibility

IoT is touted as being the next game changer in the digital world. Many apps provide compatibility across other devices as well. Wearables are gaining popularity among the current generation of users. Developers can improve customer experience by providing easy access to their app without having to use their smartphone. For instance, an app compatible with a smartwatch allows you to view the grocery shopping list and mark items as they are put in the shopping basket.

#4 – Incentives

Providing incentives to perform certain action increases the likelihood that people will take actions. Incentivizing user action such as app installs, sharing, purchase, consumption, and feedback will yield better engagement. Apart from this, gamification with point system works best for improving engagement.

For more information on increasing mobile app usage and improving customer experience

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Why it’s Time to Adopt Pricing Analytics

A modern-day consumer has multiple options to choose from the competitive market. Innovations brought about by a brand is being easily imitated, and the level of product differentiation is declining. Companies these days are battling out on the price front with competitive pricing, seasonal discounts, promotional coupons, and flexible financing. However, competing on the price directly affects the revenue, so companies should look at different avenues to maximize revenues from pricing.

Organizations have a large repository of data available to them including historical price and sales figure, price and demand fluctuations, seasonal demands, consumption patterns, and price sensitivity data. The problem arises when companies do not have the necessary time, resources, or expertise to materialize the data into strategic decisions. Pricing analytics assists the company in making effective pricing decisions to increase the profit margin; thus, contributing to the ROI.

Optimal Attainable Pricing

With the help of historical data, price sensitivity data, and consumer behavior data the price point of each product could be dynamically set to attain the best price possible. Budget airlines have been using pricing analytics and big data analytics to increase the revenue from each passenger by dynamically changing ticket prices every minute. For instance, the analytics tool can identify that historically there has been a surge in the demand on a particular date, and increase the ticket prices accordingly. When the seat remains unsold, the tool will automatically analyze the demand and reduce ticket prices to ensure sales.

Promotional Planning

Companies can get valuable insights on their historical promotional efficiency and make adjustments to their new promotional campaigns. Pricing analytics tools are so complex that it can test out the effect of promotions on the demand on a smaller scale. Then, by running the predictive analytics tools, it can automatically provide promotional offers for a price-sensitive segment and roll out premium promotions for value-seeking customers.

New Product Pricing

The problem with new product pricing is that if the product price is too high, it won’t sell and if the price is too low, companies lose out on revenue opportunities. Companies rely on traditional methods of pricing by taking into consideration prices of similar products and pricing it lower than those products. Using pricing analytics, companies can set the best price point for the new product in order to maximize revenues and employ a better price skimming strategy.

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Track your Customer Lifetime Value to Improve Marketing Performance

In the age where brands have taken the spotlight over the core product, it is becoming increasingly important to measure customers’ spend on brands. Companies are also rolling out loyalty offers and various promotional schemes to fight over a customer with their competitors. But this battle can prove to be a costly affair if they end up spending more than what they could ever earn out of a single customer.

Estimate Marketing Spends

Brands are fighting each other with massive marketing spends to gain the attention of the customers as they have a wide variety of options to choose from. Customers are offered freebies, discounts, promotional offers, coupons, and a host of other benefits to give their brands a try and build loyalty. In the quest to fight for a customer’s share of wallet, companies might end up spending vast sums, which cannot be recovered. Customer lifetime value calculation offers a way for such companies to estimate the revenues generated by a customer over their lifetime so marketing spends can be optimally allocated.

Enhance Retention

A general consensus in the marketing world states that it costs a company five times more to acquire a new customer than to retain one. It becomes necessary to calculate customer lifetime value to optimally budget customer retention strategies and programs. For instance, customers leave an internet service provider when he gets a better rate elsewhere. If companies get proactive and are aware of the situation, they can offer the customer a free upgrade to the better package. Calculation of customer lifetime value can give an accurate figure of potential future revenue so they can decide whether a free upgrade could be offered.

Boost Revenue

Customer lifetime value calculations can also be used to boost revenues with the use of analytical tools. Companies are always faced with decisions such as whether to spend the available resource to capture new customers or roll out offers to retain the current one. Proper use of analytics tools can boost revenues for the company by analyzing the impact of decisions on revenues. Here’s a look at two scenarios where customer lifetime value calculations could be used to boost revenue:

The company can thus choose to invest in retention programs rather than improving the profitability to boost the total revenue.

To Identify the Right Customer

In most businesses, a small minority of the customer accounts to a major portion of the profits, following the famous 80-20 rule. Companies may still decide to retain customers who yield lower profits for volume sales. In extreme cases, some customers can force businesses to spend a lot of resources with little or no gains in return. By using customer lifetime value calculations, such customers can be identified, and companies can then decide to either fire or de-emphasize them.

To gain more insights on how to track customer lifetime value
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How Quantzig helped a Global Conglomerate Increase Sales by More Than 50%

In today’s fast-paced environment, most vendors are looking to leverage technologies such as web analytics to minimize operational costs and maximize ROIs. Web analytics involves the use of information to track the referrer, search keywords, identify IP address, and track activities of the visitor. By accumulating such information, a marketer can improve the effectiveness of their marketing campaigns, infuse creative content, and create an effective information architecture. In any organization, web analytics in the form of effective advertising, newsletters, and site design helps increase traffic and enhance sales performance. Consequently, the use of robust analytics in marketing activities like email advertising campaigns can help improve customer engagement can also assist the organization in attaining the optimal performance and the desired goals.

Quantzig’s web analytics solution helps the client understand the behavior of the visitor, source of visit, pages viewed, and actions taken on the site. Additionally, our web analytics solution helps measure a plethora of information such as web traffic, visitors count, track bounce rate, identify exit pages, and optimize marketing campaigns.

The Business Impact

A global conglomerate was facing challenges understanding the factors hampering their sales performance. The client also wanted to gain an understanding of the possible ways to improve their sales performance by discovering appropriate tactics among the pool of analytics. The client also wanted to reduce the cost per acquisition and increase ROI.

Our Approach

To address the client’s specific business requirements, Quantzig’s team of web analytics experts collated information obtained from various sources to perform an analysis of the site and measure the website performance. The experts also collated information on how the users accessed their website, the user behavior, including the on-site interaction with key website features.

Sales01

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Web Analytics Solution Benefits

Increased traffic from generic keywords
Growth in market share
50% uplift in ROI
Improved conversion and customer experience by optimizing the website

Web Analytics Solution Predictive Insights

Leverage analytics to obtain critical and timely business decisions on a day-to-day basis
Gained rich insights into digital audiences and marketing effectiveness
Created more effective marketing initiatives, improve user experience, and optimize their digital strategies
Determined the best allocation of media and resources to drive results

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Increasing Automobile Sales in Emerging Markets through Digital Analytics

As the automotive industry is being transformed by the advent of new technologies, the manufacturers in the industry have started relying on advanced applications and services to go on par with the technologies. The manufacturers are also devising services in the form of digital analytics to understand the consumer behavior and devise effective strategies; thereby, driving sales and impacting the bottom line. Consequently, automotive businesses are also leveraging the use of digital analytics to enhance their network and reach their target audiences. In addition, automotive businesses are further utilizing digital analytics platforms such as search engines to increase visibility of their niche product segments.

Quantzig’s digital analytics solution helps the client understand the behavior of the visitor, source of visit, pages viewed, and actions taken on the site. Additionally, our digital analytics solution helps the client to optimize marketing campaigns and leverage the full potential of the digital world.

The Business Challenge

A global auto dealership company was facing challenges in striking a balance between acquiring new clients and maintaining engagement with their existing clients. The primary objective of the client was to sell inventory on a monthly basis and to keep the brand top-of-mind. The client was also facing challenges in striking a balance between marketing and branding and short-term sales volume.

Our Approach

To address the client’s specific analytical requirements, Quantzig’s team of digital analytics experts organized digital marketing campaigns that targeted individuals based on the channel they were likely to respond to promote both new vehicle sales and existing vehicle services. The channels leveraged in the marketing campaigns were in the form of direct mail, email, mobile, and desktop, and display ads.

Automobile sales

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Digital Analytics Solution Benefits

Generated considerable amount of revenue and service transactions
The client was able to acquire new customers and retain existing customers
The campaign also produced an estimated ROI in return for every dollar invested in digital ads
Promoted both vehicle sales and existing vehicle services

Digital Analytics Solution Predictive Insights

Promoted different brands of cars
Identified the potential consumers who were intending to purchase the car
Emphasized on the importance of acquisition and retention
Refined the targets and launched additional digital marketing campaigns
Identify the right person, right channel, and increase the marketing ROI

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Why Hasn’t Marketing Mix Modelling (MMM) Advanced Much Since its Introduction?

Marketing Mix Modelling (MMM) is transforming a classical adage that half of the advertising spends are being wasted, with the problem being the inability to identify which half. An enormous amount of data is being generated every year to assist marketing managers to make decisions on the optimum utilization of marketing budgets. By analyzing data on multiple marketing spends and its effect on sales, marketers can allocate budgets efficiently and devise an effective marketing strategy. Marketing mix modelling has been assisting marketing managers in formulating marketing plans with the help of valuable analytical tool to optimize the marketing mix to achieve increased sales value.

Since the time marketing mix modeling was first used during the early 90’s, it hasn’t advanced much regarding issues covered and underlying methods used. Here are some of the reason its growth has been hindered:

The Attribution Problem

Marketers are equipped with an arsenal of tools to improve their brand’s performance. These tools do not work in isolation, but rather the synergy between them is what causes a brand to succeed in the marketplace. Marketing professionals are always posed with the same problem. If there is an increase in sales or other metrics, which marketing or promotional tool should it be attributed to? Is the increase in sales caused by increased advertisement spend or a reduction in price? This can pose to be a roadblock during the resource allocation process. However, with the advent of digital technology, attribution models like first interaction, time decay, position based model, and backward looking last click attribution seeks to resolve this problem area.

How to Quantify this Information?

Insights obtained from marketing mix modelling depends heavily on the quality of input data. Abundant information can be captured with the increasing prominence of big data. One of the biggest challenges in this area is the measurement of unquantifiable information. Marketing indicators such as customer satisfaction, brand image, emotions, customer feedback, along with observational tools like eye tracking, video, physiological measurements, tracking, facial expressions analysis, and head movement cannot be expressed in terms of numbers. Marketing mix modelling does not consider such information unless it can be quantified.

The Case of Marketing Myopia

A brand is created by years of deliberate and skillful marketing efforts. Marketing professionals often attribute a brand’s success to short-term effects of media and marketing efforts. Recent marketing activities may increase brand value in the short run, but a brand’s real value is determined by its consistency, relevance, and distinction over the long run. Marketing mix modelling often struggles to adjust this long-term significance accurately.

Marketing experts have come up with various models to address these issues, offering a vast scope for improvement in marketing mix modelling. Digital marketing has also made contributions in this field by providing massive amount of data and acting as a field to test products and brands.

To gain more insights on the trends in marketing analytics

Consumer Analytics– Online Retail’s Bread and Butter

Retail is the fastest growing and dynamic sector with evolving trends and increasing competition, particularly in the online retail market. Thanks to the ever-changing consumer preferences in terms of products and services, shoppers tend to expect a lot from the retailer’s end, for example personalized experiences, unparalleled customer service and real-time information.

Today, analytics is way more than just about gathering information and monitoring. It can add value to a business in terms of new product development and service offerings to its customers, and improve the organization’s decision making process. The sole purpose of customer analytics is to analyze historical as well as real time data to predict trends beforehand and accordingly devise sound business strategies. Retailers must leverage the data at their disposal to unearth and pursue potential opportunities to drive growth in an efficient manner.

Are you still at the crossroads with regards to the usefulness of consumer analytics in online retail? We give you three reasons why this is what your business needs:

1) Predictive Search

They say, first impression is the last impression and therefore, a retailer must make sure that the first touchpoint of interaction – site search – with the customer is seamless and intelligent enough to predict what the customer is looking for, aided by historical and real time data as well as previous browsing history.

2) Personalized Experience

Retailers, in order to entice customers to visit their website and boost their sales, can leverage on analytics to personalize the customer experience. Additionally, a customer may interact with the retailer from different touchpoints, which means that the online retailers must collate and process real-time data from all incoming sources so as to offer personalized content and promotions to each individual customer.

3) Pricing Analytics

Analytics and big data help determine the pricing strategy keeping in mind sales demand to maximize revenue and profit. It takes historical and real-time data from various sources such as competitor pricing, sales and customer actions to give the organization a competitive advantage.

4) Supply Chain Management

This helps retailers understand consumer demand thereby, managing the supply chain process. It assists procurement in planning and forecasting, sourcing, fulfillment, delivery and returns. This helps the business to provide customers with information regarding the availability of products, and track the status and location of their orders. It also supports merchants to minimize operational costs, reduce inventory and storage costs, predict the revenue stream from products and maximize profit margins in the long run.

Thus, we conclude that marketing analytics will create sustainable competitive advantage for online retailers to execute strategic business decisions to improve customer experience and business performance.

The Quantzig Plus Point

We, at Quantzig, track latest developments and innovations in the industry through different sources and methodologies. Reaching out to key stakeholders and marketing experts in order to understand the market conditions, we help clients understand and identify fluctuations in consumer interests and devise insight based marketing tactics and strategies to stay abreast of the competition.

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:

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.

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.
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.
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.
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.

Tag: consumer behavior

Four Ways to Improve Customer Experience and Engagement for Mobile Apps

#1 – Smart Notification

#2 – Invest in User Interface and User Experience

#3 – Cross-Platform Compatibility

#4 – Incentives

Why it’s Time to Adopt Pricing Analytics

Optimal Attainable Pricing

Promotional Planning

New Product Pricing

For expert advice on implementation of pricing analytics:

Track your Customer Lifetime Value to Improve Marketing Performance

Estimate Marketing Spends

Enhance Retention

Boost Revenue

To Identify the Right Customer

Increasing Automobile Sales in Emerging Markets through Digital Analytics

The Business Challenge

Our Approach

Want to learn more about our analytical methodologies?

Digital Analytics Solution Benefits

Digital Analytics Solution Predictive Insights

Want to know more about big data analytics solutions?

Related Articles:

Why Hasn’t Marketing Mix Modelling (MMM) Advanced Much Since its Introduction?

The Attribution Problem

How to Quantify this Information?

The Case of Marketing Myopia

To gain more insights on the trends in marketing analytics

Related Articles:

Consumer Analytics– Online Retail’s Bread and Butter

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