jencyjane

[jencyjane]

“More Productive. Efficient. Cost-Effective.”: You Can No Longer Afford to Ignore Business Intelligence

Business intelligence is the capacity for gaining knowledge about your business and its environment and using it to make better business decisions.  The aim of gaining business intelligence is to avoid the costly risk that comes with instinct. Instead, it endows a business with the ability to reliably predict the outcome of its decisions.  

Intelligent businesses are smarter, more productive, more efficient, more cost-effective, and therefore more successful.

I. Higher accuracy 

Business intelligence is characterized by fact-based decision-making instead of gut-based decision-making. Instead of guessing what, how, and whom to sell, intelligent businesses first set a well-defined goal. Then, they collect high-quality market and customer data and analyze it to yield actionable insights.  These insights inform every decision that shapes their sales and marketing strategies, for example.  

What's incredible about such a strategy is that it can adapt to changes in the market.   

Whether it is fickle customers or new technology, these changes are reflected in the new set of collected data, which when analyzed will produce new insights, which can be used to shape a new strategy.   

Secondly, business intelligence enables you to create personalized customer experiences — something customers cannot get enough of. Every time customers engage with a product or service, they generate unique data which tells something about their preferences. The data can be used to inform marketing campaigns or sales pitches or online experiences that are tailor-made for them. 

And when they actually are, they generate more unique data, making the data set even more strengthened, making the following experiences even more effective! The result is hyper-targeted sales and marketing.

II. Higher output 

People are intelligent. Creative. But they are also slow. Further, it’s been consistently demonstrated that our mental state has a big impact on our performance. On the other hand, computers might not be intelligent and creative. At least not today. But they are fast. Also, they lack a mental state. They are either on or off.

So, what happens when we combine their best qualities? We get intelligence and creativity, accelerated and scaled. For a business, this represents a breakthrough.  

Intelligent businesses leverage the speed of technology to automate manual, repetitive tasks so that they can leverage the creativity of their employees to solve more complex problems. They are characterized by smart decision-making whereby inefficient tasks can be delegated to a Robotic Process Automation (RPA) software, while they can focus on business-critical work. 

III. Higher savings 

What do you get when you combine maximized output and hyper-targeted advertisements? Savings.

Maximizing productivity — or decreasing inefficiency — means getting more bang for your buck. And fact-based marketing, for example, means not taking unnecessary risks that threaten losses. The two can combine to increase revenue dramatically, especially in the long run.   

Unsurprisingly, business intelligence solutions are in ever-increasing demand. Businesses, realizing the unprecedented gains, are now rapidly adopting data-driven practices, keen to solve complex, costly problems with fact-based solutions.

[jencyjane]

The deadly heat wave sweeping the Pacific Northwest and Canada has reportedly caused more than 600 casualties, in total. Now, a study (World Weather Attribution) published by an international team of 27 climate scientists has found that the extreme, record-smashing event would have been “virtually impossible” if it was not for climate change

[jencyjane]

What is the difference between Data Governance & Data Management?

Data governance and data management are two different terms with one goal – to ensure good quality and trustworthy data to empower organizations. There is a fine line difference between the two terms that are often confused to be same.

Data governance focuses on data owners, organization structures, rules, policies, metrics, and many such whereas data management focuses on the technical implementation of data governance.  

Here’s brief explanation on the subtle difference between data governance and data management.

What is Data Governance?

Data governance defines how data is to be accessed or treated. It is a broader data management strategy that regards data as an asset and refers to the ways it should be handled and protected within an enterprise. Basically, data governance is the amalgamation of people, processes and policies and caters to the usage of an organization’s data.

Why Data Governance is important?

Data governance enables companies to determine the usage of data for financial benefits and mitigate risks due to poor data. It goes beyond IT and involves stakeholders to determine a holistic way to control data assets. Also, it helps businesses in overcoming the inefficiencies due to siloed and fragmented data and ensures the safety, reliability, and trustworthiness of the data stored in their repositories.

Above all, data governance is a prerequisite for businesses to better comply with emerging data regulations like GDPR (General Data Protection Regulation), CCPA (California Consumer Privacy Act), etc.

Benefits of Data Governance

Reinforce data security and maintain regulatory compliances

Define policies and rules to streamline data utilization

Define metrics to standardize data management  

Create roles and accountabilities for data management

Enhance data accessibility to improve performance  

What is Data Management  

Data management refers to the implementation of architecture, processes, procedures, and technologies to achieve data governance goals. It comprises policies and procedures to carry out data collection, classification, quality control methods, metadata management, and integration frameworks appropriately.

Benefits of Data Management  

Helps collect, structure and organize data

Maintain data integrity and avoid technical mishaps  

Helps increase productivity by streamlining the data flow within an organization

Improve data quality through cleansing and standardization

Retention policies to archive less frequently used data

Data Management Vs Data Governance

In simple terms, data governance refers to the blueprint of any building while data management refers to the physical construction of the building. Buildings can for sure be constructed without a blueprint, but they are to lack efficiency if done so. Similarly, data governance is just a documentation without data management.

Also, data can never be governed if it isn’t defined. Hence it is essential to know what the data is, how it is collected, where it is collected from, where it is currently stored, and how it can be accessed. Thus, data governance and data management are interlinked, and one may not be as powerful without the other.

Finally

The consolidation of data governance and data management is necessary for businesses to fly through the data cloud swiftly and steadily and reap the benefits of big data in real-time.  

[jencyjane]

Experiential Marketing: Connect and Interact with customers creatively

Marketing, one of the crucial elements in driving sales and business value, has a long history of evolution. The advent of digital transformation and customer-centricity has revolutionized Marketing once again in modern times. Marketing, no longer just refers to promoting or selling products or services. It has evolved beyond that. Modern-day marketing mainly focuses on connecting and interacting with the audience in a way that will leave a remarkable impression about the brand, product, or service on them.  

While creating an exceptional marketing strategy, that will benefit a brand, is in itself a tedious task, what’s even more concerning for current-day marketers is brainstorming for ways that will help grab consumer’s attention, particularly the Millennials and GenZs who contribute to more than half of the potential consumer community. In current times, the experience is all that matters to consumers.

In this article let’s discuss about a type of marketing that primely focuses on customer experience.

What is Experiential Marketing?

Experiential Marketing also known as Engagement Marketing or Live Marketing, is a marketing strategy that aims to provide a real-life customer experience that will be remembered. The key goal of experiential marketing is to create a close bond with customers by engaging with them through creativity.  

Why is it important?

With the help of experiential marketing, brands can form a memorable and emotional connection with their customers. This strategy has proved to be instrumental in fostering customer loyalty and improving customer lifetime value (CLV) as it appeals to the emotional aspect of a consumer. In fact, 77% of marketers are using experiential marketing as a core part of their advertising strategy (EventTrack). 65% of brands claim that experiential programs impact sales directly (EventMarketer).

Also, combining experiential marketing with digital marketing can help businesses increase brand visibility online.

Striking Experiential Marketing Examples

Campaigns using experiential marketing can come in various forms like in-person events, in-store events, installations, trade shows, product rollouts, etc. Leveraging frontier technologies like AI and data analytics, brands can extract consumer insights more granularly and determine which form of experiential marketing will best suit their product or service.

Here are a few examples of outstanding experiential marketing that not only impacted customers but also proved elemental to boost event ROI:

Volkswagen Piano Staircase: One of the well-known car companies, Volkswagon, created “piano” stairs, right next to the escalator in a subway stop, in Germany. The key objective was to drive people’s behaviour with an element of fun. As a result, more than 66% of people choose stairs to the escalator. The commuters had a great time playing their own tunes while striding up and down the stairs. Though it was very unusual for a car company to use musical steps for their experiential marketing strategy, the campaign soared as it resonated with a simple yet significant emotion of humans – having fun. Volkswagen’s musical steps clearly exhibited that products aren’t always essential for an experiential strategy. The strategy is worth it as long as companies can associate their brand with their customer emotions.

Gatorade Combine: A brand that is closely connected with athletes, Gatorade, offered a completely athletic experience for its consumers at SXSW in 2017. Gatorade Combine aimed to offer an experience of the future of for athlete evaluation. The experience provided an opportunity for consumers to test their overall athletic abilities. Consumers experienced testing from athletic innovators like Kitman Labs, STRIVR, and Sparta Science for various abilities like reflexes, flexibility, etc. The accurate and data-rich test results actually made consumers feel like professional athletes. The main takeaway here is, besides entertaining, experiential marketing is all the more effective when it offers something that is of actual value to the consumer.

Summing Up

True magic happens when a company can go beyond offering attractive offers or samples and provide consumers an immersive experience with the brand. Experiential marketing can enable a company to stretch beyond its PR stunts, display ads, or promoted social media ads and deliver a successful campaign that will stay in the minds of consumers for a long time and create an inextricable bond with the brand.

[jencyjane]

Data Science & Future of Market Research

Once a buzzword, today a common term, Big data, is disrupting business operations in many exciting ways. Market research is no exception. Besides, the application of data science has enabled advanced market research and influenced business growth greatly. While the combo of data science and big data fuels market research, present-day rumours suggest that ‘Big data and data science will replace market research’.  

Well, this piece of content will walk you through how such a situation is far from happening either now or in the future, and explain how data science and market research will collaborate closely for business development.

To start with, let see how market research is benefitting from data science

Today’s world is inundated with data. The evolution of smart devices, IoT, internet and social media platforms, and smart cities have their fair contribution to the growth of big data. The abundance of data is and will be constantly growing in this digital era. Traditional market research surely lacks the capabilities to cope up in this hyper-connected and fast-paced world, particularly in terms of speed and time to process the behemoth data.  

However, the availability of sophisticated tools is making it possible to process and analyze the high volume, high velocity, and high variety of data today. Gleaning insights from this data enable in spotting trends, pinning hidden patterns, and making futuristic decisions.

Big Data comes with its own downside

The absence of context and connectivity makes big data meaningless. To explain more clearly, consider a situation where there is a peak rise in the customer attrition rate. Through big data, the company can identify when this started happening and what are the primary factors driving the situation.

Let’s says the key factors driving this situation are bad customer service, high pricing, and similar product launch. Here, the key factors indicate ‘what’ has happened and fails to explain ‘why’ this has happened. Thus, Big data can enlighten ‘what’ in a situation but not ‘why’.

Why Big data can never replace market research

Leveraging big data market research helps comprehend why customers do what they do. Apart from understanding customer behavior, it also helps comprehend what they expect from brands and products.  

Through market research, the following measures can be implemented to mitigate the customer attrition rate and improve customer acquisition and lifecycle.  

Focus on customer engagement to improve customer service

Provide offers and optimize pricing

Collect customer opinion on a similar product, analyze metrics, and make a data-driven decision to tackle the situation

The above paradigm shows how big data and market research complement each other. Big data can never replace, or force market research into obsoletion because it lacks context and connectivity by nature.  

Big data empowers market research by reducing dependencies on surveys and offers an abundance of data through the internet and social media, from which actionable insights can be extracted and applied to build befitting strategies for the data-driven decade.

Facebook is a real-time example to understand how much one can benefit from big data and market research. The most popular social network has over 2.4 billion monthly active users, which clearly indicates the plethora of data that it possesses in-house, but still uses polls and surveys research panels to observe people’s attitudes and understand their behavior to improve their stories and ads.  

What’s in the future of market research and data science

Big data can never replace market research. Rather they both will be collaborating hand-in-glove to breakthrough trends and help companies improve profits and establish a competitive edge. Additionally, data science is constantly advancing and the advent of predictive analytics will take market research to the next level.

As businesses are striving to perform targeted marketing and provide personalized customer experiences, big data and market research is a classic combo to achieve business goals and amplify profits in the present as well as in the future.

[jencyjane]

Customer-Centric Strategies to Fuel Retail Sale

“Customer centricity is a strategy that aligns a company’s development and delivery of its products and services with the current and future needs of a select set of customers in order to maximize their long-term financial value to the firm” ~ Peter Fader, Professor of Marketing, Wharton University

In today’s fragmented market, where consumers are in control of changing market dynamics, it has become essential for retailers and suppliers to be more nimble and customer-centric to accelerate product development and sale.

Here, let’s take a look at customer-centric strategies that can drive productivity and retail sales.

Predict your Consumer with Sophisticated Customer Analytics tools

 “In the age of the customer, executives don’t decide how customer-centric their companies are — customers do”~ Kate Leggett, Analyst (CRM), Forrester

Consumers today anticipate highly-selective and value-specific products along with personalized shopping experience. Retailers and Suppliers struggle to deliver products that meet customer needs with effective customer experience mainly due to their ignorance of customer engagement.

Though retailers and suppliers today collect consumer behavior data from various social and digital sources, they had been struggling to deliver real-time customer experience due to a lack of high-end technology tools.

Consider this scenario, one consumer group watches hockey on their iPads, while another favors television. Segmenting audiences by predicting consumer behaviors could necessitate marketing different products or use different messages for each medium.  

“Analytics today are no longer simply descriptive. They are predictive- and increasingly prescriptive.”

Fortunately, the innovation of Artificial Intelligence (AI), Business Intelligence (BI), and Machine Learning (ML) can aid to this struggle with an efficient consumer behavior examination and enable 360-degree consumer insights; narrowing the gap between customer data and actionable insights;

 Sketch your Retail Strategies with Collaborative Planning

“According to A.T. Kearney, companies that collaborate have experienced 10%–15% growth in top-line performance, increases of 40%–60% in the rates of new product launches, and a 20% decrease in inventory”

A collaborative approach is as imperative as your costumer. Combining CPG company's knowledge of consumer behavior, especially as it relates to product category, with the retailer's deep data on its own shoppers will benefit the two parties to have a better chance of understanding and influencing today's often complex path-to-purchase.

 This collaborative approach to understand consumer behavior and enhance the customer-centric approach not only enables trade partners to give retailers more knowledge of their categories but also aids suppliers to

Gain more understanding of their products.

Restructure budgets to support more performance-based funding models versus simply rewarding top tier accounts with “grandfathered” budgets.

Identify barriers around execution, promotional ROI, and competitive advantage

 Provide a Personalized and Omnichannel experience

“Personalized marketing and advertising are not about sales. It’s about building a relationship with the customer.” – Julian Hillebrand, Author, and Keynote Speaker

Customer’s today are no more looking for good shopping experiences; rather they are looking forward to ‘ personalized’ shopping experience. Deriving shopping journeys by mapping customer personas will not only enable customer engagement acceleration but also path-to-purchase optimization.

Also, creating a shopping experience irrespective of the channel is significant in today’s customer experience as they don’t prefer being stuck either to mobile devices or live agents; additionally, they also look forward to phygital (physical and digital) shopping experience. Hence facilitating an omnichannel experience is significant for a customer’s personalized experience.

Summing UP

Gone are the days when brands told people why they need a particular product or service. Today the tables have turned around where consumers identify their own needs and look for a product regardless of brand or distribution channel. Leveraging a customer-centric approach with sophisticated customer analytics tools will enable appropriate merchandise to market faster and more cost-effectively.