Introduction:
Marketing is a process which fulfills human and social needs. The core concept of marketing is to satisfy customers. Recent trends are driving this concept into a more integrated format. Once there was a time where innovation, information, ambitions, specifications, preferences, choices, opportunities were limited and markets were able to function with limited numbers of marketers and their ideology. This concept is facing change on the one hand with unprecedented growth and the potential impact of MSME’s, especially startups in the market. All this is impacting the way people consume. Starting with the core proposition of marketing and the product-based framework of the 4Ps morphing into 7Ps for services, other marketing paradigms such as holistic marketing, societal marketing, cause related marketing have emerged. The simplistic premise that satisfying customers by supplying good products, reasonably priced and with a strong distribution network will no longer help a marketer retain today’s customer. There is a need for continuous evaluation of the customers and their movement and marketing therefore becomes more customer-centric and customized than ever before. To survive in this competitive market, the marketer of today has to be constantly on his toes, trying to develop competitive advantages and core competencies. Today’s customer is fickle, and rarely stay with the same brand for long, and customer attrition is threatening to overtake customer retention, and the market is increasingly turning volatile in nature. It is thus not surprising that in certain contexts the strategies used by today’s marketers fail to display a deep understanding of the market and its customers. In this situation marketing analytics can play a huge role in gauging the market ad enable reliable predictions for the future.
Marketing Analytics overview:
Marketers of yore were highly dependent on market information and research outcomes for taking their business decisions. But in today’s world there are colossal sources of information from different perspectives and each one has their own potential use and impact. It is quite difficult for a marketer to delve into each area and glean critical information without the use of specialised tools and lagging behind in this area may doom them to failure. Marketing analytics, which is a process of manipulating and interpreting data, which offers a way out to take better marketing decisions. It helps marketers to understand the dynamics of their business, anticipate market shifts and assess risks. When marketer takes any kind of business decision, there is a dire need to anticipate the outcome of this decision. To do that there is a need for judgment using past activities as the benchmark and understand the impact of changes in the immediate, medium term and long term future. The challenge is to match these three and anticipate the direct and indirect effects in the marketing outcomes. These are usually categorised as descriptive, predictive and prescriptive analytics. Descriptive analytics helps the marketer to understand to what happened in the past and alerts the marketer regarding the actions needed to minimize the negative impacts. Predictive analytics is perhaps the most important tool to identify what will happen next and carry out ‘what if’ analysis. These two questions can be effectively addressed by using predictive models and randomized testing. Thus, if we reduce the price of a product can it lead to increase in customer buying or if marketer increases the price, or promotion through different media or reduction in some content what could be the effect on business? The major advantage of analytics is to handle the market data coming from different sources and in different formats. It enables the marketer to clearly distinguish between past, current and future trends, allowing him to forecast consumer behavior before it actually occurs. By using audience profiling data in terms of geographic, demographic, behavioral categories, it proceeds to predict what customers want, allowing marketers to be proactive, upselling products, creating long-term relationships with consumers and determining market shifts before rival brands. We can summarise that marketing analytics as below.
- Data driven market prediction and decision.
- Gives alerts marketer based on past records (Descriptive analytics).
- Helps to take decision looking into current trend and policy implementation (Predictive analytics).
- Helps to identify best possible opportunities through trial and error (Randomized effect),
- What is the best that can be done (Prescriptive analytics)?
- More focused decision making by using different characteristics of market/ consumer data.
- Helps to improve business forecasting.
Major Functional areas of Marketing Analytics:
Day by day the role of analytics is expanding in different areas of business, led by large corporations who applying analytics to their decision are making process as never before. They see this process as much more efficient compared the traditional way of prediction and precautions in business decisions. The major areas, where analytics is finding use are development of branding in term of brand personality, brand equity and brand architecture. The other areas of deployment are customer management, product design, price strategy, distribution system, and promotional development, and customer service. Companies are thus using analytics to enable faster and fact based decision making and this is turning point for he marketer to enjoy competitive advantage in market. Data driven decision making helps organizations not only to make better strategic decisions, but also enjoy high operational efficiency, improved customer satisfaction, and robust profit and revenue levels. In terms of customer acquisition and retention, the analytics provide a huge positive impact improving customer profitability and reduce churn. Thus, marketing analytics helps marketers to
- Develop effective branding strategy
- Identify prospect in terms of customer management
- Enable faster and fact based decision making
- High operational efficiency and customer satisfaction.
- Right decision in right time.
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