Advanced Analytical Techniques. Rethinking traditional consumer segmentation The good old concept of segmentation, targeting and positioning framework, has stood the test of time and have helped marketers take strategic business decisions.
These business leaders have routinely used demographic analysis to help craft a brand’s message, positioning, and marketing. By grouping consumers mainly by age, geography, ethnicity, gender, income and family status, marketers have been able to draw conclusions about that group’s shared interests and consumption behaviors. But today, do new age consumers belonging to the same target segment, behave alike? Probably not. By confining the consumers within the demographics conventions, we have instinctively assumed that everyone within the same group has similar needs. Conversion Rate Optimization. The Digital World One of the defining trends in the recent years has been the colonization of the real by the digital.
The rise of social media, smart phones, e-mails and blogging clearly indicate that the world is moving more and more towards digital. With an increasing number of businesses going digital in order to reach more customers, empower them, reduce cost, and save time, they have a need to invest more on Digital Marketing activities such as Search Engine Marketing (SEM), display targeting, social medial advertising, email campaigns to increase traffic to their websites.
Social Media Analytics. In this issue of our #highondata series, Dave Sheluga, Director of Consumer Insights at Ardent Mills, discusses how social media analytics have changed marketers’ understanding of their customers, and their ability to shape the future of the CPG industry.
About two years ago, we saw an increase in demand for using social media data to enhance understanding of trends seen in secondary research data. What were the benefits marketers saw in doing this? The marketplace around consumer packaged goods changed abruptly in early 2011. Marketers found that traditional marketing tools that served them well for 40 years were no longer working so well. And market researchers discovered the need to view the marketplace more broadly. Customer Lifetime Value. Customer Lifetime Value (CLV) is the estimated net profit a business expects to get from the entire duration of its relationship with a customer.
A high CLV is desirable as it implies increased profits and higher levels of customer engagement. Analytics is today used by mature organizations across the different stages of the customer lifecycle in order to increase CLV. Acquisition: While customer acquisition is a key performance indicator for many businesses, many companies fail to measure two important parameters – the Cost of Acquisition and projected Lifetime Value. Spending too much money acquiring customers with low lifetime values will corrode a company’s profitability. Chewing Gum Usage in USA. High Net Worth Customers. In the halls of marketing fame, customer acquisition stories get all the attention while those involving retention are rarely discussed with the same fervor and enthusiasm.
Yet, most marketers will admit in private that customer retention is the single most important priority and an integral part of their strategy, which significantly impacts their bottom line. According to global consulting firm Bain & Company, it costs six to seven times more for an organization to acquire a new customer than to keep an existing one. Increasing customer retention and loyalty is particularly relevant for retailers as they attempt to grab market share in a competitive environment. But how exactly can retailers identify and create loyal customers? Mere numbers — visits to a website, for example — do not tell us the full story of brand affinity unless they are also accompanied by other critical indicators regarding attitude or perception, and sentiment or advocacy toward the brand.
Optimal Analytics Maturity. Note: Krishnan Venkata, Vice President- US West presented a paper on ‘A Roadmap for Optimal Analytics Maturity’ at the Chief Data And Analytics Officers Exchange in California, early this year.
A summary of his presentation is captured in this blog post. Social Media Analytics. Being an analytics professional, I like doing interesting analyses on various hypotheses I have regarding what is going on in the world.
Most recently, I’ve been thinking about how there is a mismatch between what the businesses portray and what the consumers actually feel about brands. To test this hypothesis, I analyzed 100,000 tweets of four brands: Sears, Wal-mart, Kroger and Macy’s. Predictive Modeling. In order to provide accurate digital insights that are representative of the browsing population across devices, companies are increasingly looking to collect consumer behavior data from multiple sources.
They then look to blend those sources into a single digital panel, and use algorithms and advanced analytics techniques to normalize the data to the population as a whole. Digital panels track every click of the panel member, search key words and can help understand path to purchase better (either in their digital property or at competitors property). Effectiveness of Campaigns. Data specialists add value to virtually every department within an organization.
In sales, they can analyse past and current sales to predict future demand, determine pockets of heavy demand and areas with high potential to target customers well. In the marketing department, they can analyse social media trends, effectiveness of campaigns and optimize return on investment for different marketing media used. In the operations department, they can help make supply chain decisions, help in procurement and determine best routes for raw material and finished goods. Predictive Analytics. Modern Marketer’s fascination with mobile is not new – the power of this channel has been measured, analyzed and talked about for quite some time now, and the focus is certainly not going away.
The value of this channel as a business tool is undeniable. According to Gartner, by year-end 2016, more than $2 billion in online shopping will come from mobile digital assistants. Data Visualization. When it comes to data collection in today’s digital era, the sheer volume of available data is staggering. Can the average business do anything with this volume of data? To be successful, you have to pay attention to the available data and see how you can extract the most out of it. But how? Data is only useful if you have a way of managing it and turning it into insightful information. Social media listening Tools. eBay Using Analytics. In this inaugural Q&A of our new #highondata series, Zoher Karu, Chief Data Officer, eBay, shares how the company is using analytics to drive competitive advantage. What are the most significant ways in which eBay is using analytics to gain competitive advantage?
Social Media Listening. Dave Sheluga of Ardent Mills (Director- Consumer Insights), Jen Randle of Whirlpool (Global Director-Innovation), Krishnan Saranathan of United Airlines (Managing Director- Customer Data and Optimization) and Vicky Robertson-Mack of Sears Home Services (Director- Marketing) came together to share how their organizations use data to gain a competitive advantage and how they are preparing for the future.
While the speakers were all from different industries, they were unified by a strong focus on the end consumer. Social media analysis is today an integral part of market research. It provides deep and granular insights into consumer preferences by ‘listening in’ to natural conversations. Advanced analytics organizations are using it not just to understand their customers but to use that understanding to drive innovation. Web Analytics. Millennial Consumer. Shopping behaviors, buying trends and patterns are changing at a rapid pace across the US and the global marketplace; brands that were once iconic, now struggle to stay afloat in markets that are sometimes almost single-handedly driven by millennials.
According to a recent Yahoo survey, millennials will have $1.4 trillion of spending power in the US by 2020. This would make them the single largest consumer segment. So exactly how can brands get millennials to sit up and take notice? How do they get this notoriously ‘tough crowd’ to engage with them? The biggest advantage that marketers have when building marketing programs for this target audience is the huge trail of digital data they leave behind. As most new age marketers will agree, the traditional AIDA model of marketing has become irrelevant in today’s connected world; more so when dealing with the millennial consumer. Analytics plays a very important role in making a brand relevant to a millennial audience.
Analytics Organisation. Companies are increasingly relying on analytics to maintain their competitive edge. One question that needs to be addressed at the moment is, “What’s the best way to structure an analytics organization?” As organizations begin to think about structuring its analytics body, it is necessary they prepare an outline and then work towards putting the goals, roles, skills and culture in place. The protocol outlined for the analytics team must adopt the vision and roadmap set out for the organization. Predictive Analytics. Artificial Intelligence. Quantifying Bad Customer Experience. Social media listening Tools. LatentView Analytics. Analytics Techniques. Predictive Analytics. While developing or building a Predictive Model, factors such as combining an ensemble of models and techniques, cleaning out data, segmentation and definition of a clear problem statement help increase efficiencies by about 10 – 15%. The below infographic depicts the five steps that will help improve the efficiency of your Predictive Model: Improving The Efficiency Of Your Predictive Models.
Analytics Tools, Technology & Techniques. Business Management. Business management programs are designed around logic, reason and sharpening of the intellect. As students at this prestigious institute, I am confident you will rise up amazingly well to the challenge, and soak up enough knowledge in your two years here. Information of Things.
Over the last few years, advances made in the Internet of Things (IoT) has caught the attention of the tech community. Measure Campaign Effectiveness. The most common way of measuring the impact of a marketing campaign is to create a control group of customers who do not receive the campaign and compare them with those who are targeted for the campaign, the target customers. LatentView Analytics. LatentView Analytics. Business Intelligence. 360 Degree Customer View. In the real-world, its difficult to label consumers. LatentView Analytics. Social Media Analytics. Digital Payments. Business Intelligence. Artificial Intelligence. Information Analytics. Analytics Industry. Advanced Analytics. Business Analytics.
Blog around Digital Analytics, Marketing & Web Analytics.