Customers can choose to buy products online without certain sensory experiences, such as touching, smelling or tasting. Consequently, product reviews are extremely important to implement online marketing strategies. While reviews can influence customers' purchase decisions, how they affect the decisions of potential consumers in the case of a growing emerging economy such as India has hitherto not been studied. Positive and negative reviews affect the way customers understand and interpret product information. This study provides multiple methods to identify the relationship between reviews and customer decisions in the case of tier 1, tier 2 and tier 3 Indian cities. The outcomes in tier 1 cities (n ¼ 1200) reveal that reviews have a positive effect on buying decisions. Our empirical findings suggest that online reviews affect consumer attitudes and can significantly influence e-commerce sales in India.
This empirical study contributes towards identifying the effect of both fake and real discounts in the Indian marketing environment. A common but unsustainable practice in India is to increase the selling price and then offer a discount on the product. Increasing sales based on fake discount pricing strategy is a primary business development objective in India. The discounts, however, vary across store type and time and are based on product features. The selected databases were collected from the top five Indian e-commerce portals in terms of volume of sales, and from popular brick and motor outlets of tier 2 and tier 3 cities in India. The empirical results indicate that offers based on price in India had an impact of 2.8 times higher than the actual quality of the product. The outcomes suggest that marked price has a significant impact on consumer’s behavior. The results also indicate the existence of a strong correlation between trapping fake discounts and purchase by deceiving and persuading customers in India. Research is empirical in nature and respondents have been selected based on purposive sampling. The study is limited to tier 2 and 3 cities of India for 250 days, and the results are applicable to online and offline retail stores.
The paper is based on information which is a combination of store advertisement and consumers’ path inside the store along with product information. With this information, the authors find how advertisement affects the behavior of consumers when making the decision. The findings suggest that advertisement has a small impact on customers inside the stores. Null effect is determined, and one standard deviation in advertising has an impact on store traffic by 1.2%. But the impact at a lower end of the model is observed. One standard deviation in advertisement has impacted the store sales by 8.4%. Based on further data mining, the research has found that there is no significant improvement in the number of customers, but the increase in sales is because of the higher quantity of purchases by the existing consumers. However, the effect of advertisement on products placed in the same or nearby shelf is not found, the impact on product varieties in the same segment is also not found. Based on these research findings, the authors find the right approach towards advertisement.The research is limited to consumers of retail industry in a Tier 3 Indian city of a developing geographic segment only.
Artificial Intelligence (AI) has been the biggest revolution of the 21st century impacting every aspect of the business, sales being no different. The paper experiments the effect of marketing on 4500 customers using AI and humans. The outcomes of the research reveal the effectiveness of AI is the same as experienced salesmen and 2.7 times better than inexperienced salesmen is closing the sales calls. The sales graph experienced a dip by over 86.23% when it was revealed to the customer that the interface is with the machine, not humans and reduced the duration of the call substantially. The paper shows that Indians do not believe Artificial Intelligence and still prefer human interface as they do not trust machines over human emotions. The effectiveness of AI drastically reduces despite its superiority over humans in various aspects. The paper identifies the strategies to overcome the trust deficit that exists among Indian customers. The outcomes show how AI can be used, and how marketing could be done using AI in conservative markets such as India.
South Asia has seen a digital revolution in recent years. The number of persons who use the internet has risen drastically. They use it for shopping, social media and online sales. However, there exists a literature gap as far as the effect of outbound digital marketing in B2B markets is concerned. The research builds a model based on brand and consumer interactions in Indian B2B markets using a vector autoregressive model to systemically analyze the cost and outcome of digital marketing efforts by the start-ups operating in South Asia. The multivariate time series analyzed in identifying simultaneous and consistent impacts by the start-ups. We use Vector autoregressive model as it allows us to analyse the relationship among the factors as it changes over time. The research finds evidence for the conceptual framework in South Asian markets. The results prove that sales are greatly influenced by digital media, and outbound marketing efforts, predominantly word of mouth, has a huge impact in building a brand image as it spread over in the social media platforms. It is observed that the digital marketing strategies and consumer interaction are the same across South Asia, but its effect varies from country to country within South Asia thus suggesting a need of developing a new strategy in digital marketing for B2B markets.
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