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Contributors

Writers

Priscilla Thomas

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A content writer who has worked for Infosys Technologies and other technology startups in India and abroad.

Avanish Tiwary

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An independent journalist who writes on business strategies.

Priyanka Bhatacharya

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She has been covering the Indian information technology industry since its early days.

S.Sahu

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Sahu was with TCS as the editor of their house magazine before he became a freelance content writer.

Prajwala Hegde

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An independent journalist who has worked with The New Indian Express and City Today.

Rajesh Nanarpuzha

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Rajesh Nanarpuzha is an Assistant Professor of Marketing at IIM Udaipur. Previously, he has worked as a brand manager in Dabur, and as a business consultant in the retail and consumer goods domains at Cognizant and Tata Consultancy Services. Rajesh has an MBA from IIM Indore and a doctorate in marketing from IIM Ahmedabad.

Designer

Priyokumar Singh Naorem

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He is a passionate UI & UX designer who thrives on creating engaging creative solutions.

Artists

Dyuti Mittal

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A freelance illustrator, artist, graphic novelist and designer. She has designed and illustrated several book covers. Her personal illustrations so far have attempted to seize the fleeting absurdity and mood of places, things and people she encounters in a childlike, intuitive and expressive manner with closure, beauty and innocence – the things that she desires.

Sumakshi Singh

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She is an artist and an educator who has taught and lectured at The School of the Art Institute of Chicago, Oxford University, the Victoria and Albert Museum among other institutions. Her installations, paintings, thread work and sculptures have been exhibited in Saatchi Gallery - London, C24 Gallery - New York, and Museum of Contemporary Art – Lyon, among other notable galleries and museums from around the world.

Parul Gupta

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A commerce graduate from Delhi University, Parul pursued a masters in fine arts from Nottingham Trent University in the UK. As an artist, she is interested in line as a subject which has led her to follow architectural lines in built environments. She says she is also interested in how we perceive the environment that we inhabit and what happens when a subtle shift is made in things which we have been used to seeing in a certain way. We present six of her artworks here.

Shweta Malhotra

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Shweta Malhotra is a graphic artist and designer from Mumbai, based in New Delhi.
After working with ad agencies and design studios for close to 8 years, she branched out on her own and currently works independently.s Her overall design aesthetic is minimal, bold and graphic, a response to the maximalist visual language prevalent in India.

Rithika Merchant

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Rithika Merchant (b.1986) received her Bachelor’s Degree in Fine Arts from Parsons the New School for Design, New York in 2008. She has exhibited extensively since her graduation. Recent exhibitions include a duo show “Reliquaries: The Remembered Self” at TARQ, Mumbai; “Language of the Birds: Occult and Art” at 80WSE Gallery, New York; and group shows at Summerhall, Edinburgh and Artry Gallery, Kochi. Her work has been included in multiple group shows at Stephen Romano Gallery and The Morbid Anatomy Museum, New York. Born in Mumbai, she now divides her time between Mumbai and Barcelona.

Aniruddh Mehta

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Aniruddh Mehta is an artist based out of Mumbai, India. Trained in graphic design from the London College of Communications, Aniruddh is a self-taught illustrator and currently works as an independent freelance designer. He believes in finding the right balance between art and graphic design. He has worked closely in collaboration with Bhavishyavani Future Soundz, Qilla Records, Taxi Fabric, Adidas, Dell and United Colours of Benetton. He also goes by the moniker, ‘thebigfatminimalist’ and his style ranges from bold minimal forms to more intricate pieces exploring patterns and geometry.

Paramesh Jolad

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Paramesh is an artist who enjoys working in both the realistic and abstract style of painting. He loves working with water color. Featured in this issue are a set of water color works that he has created exclusively for us on the subject of digital transformation.

Concept and Direction

Nimish Vohra

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Head of marketing at Regalix, Nimish drives research in emerging technologies and customer experience, and takes a keen interest in creative arts.

Enquiry

+91 9916326475

venkatesh@regalix-inc.com

Know when a new article is published


Rajesh Nanarpuzha is an Assistant Professor of Marketing at IIM Udaipur. Previously, he has worked as a brand manager in Dabur, and as a business consultant in the retail and consumer goods domains at Cognizant and Tata Consultancy Services. Rajesh has an MBA from IIM Indore and a doctorate in marketing from IIM Ahmedabad.

The ‘number of new customers acquired’ is often considered an important growth metric. However, in isolation it is often incomplete, and many times misleading, as an indicator of the health of a firm. The reason, as Kumar, Dixit, and Dass (2016) point out, is that acquiring a new customer is almost five times as expensive as retaining an existing one. However, in the rush to bask in the afterglow of new customer acquisition, the value of retaining existing customers is often overlooked. Business to business (B2B) contexts tend to show greater vulnerability to this phenomenon. In this article, I delve into extant research to uncover possible reasons. Then, I look at Artificial Intelligence (AI) in particular, as a means to improve customer retention strategies.

The B2B environment in flux

Doney, Barry, and Abratt (2007) cite the intangibility of service offerings, complexity in the evaluation process, long-term nature of relationships and difficulty in predicting future performance as salient characteristics of the B2B environment. Adding larger purchase quantities, more frequent transactions and greater transaction values to the mix, Jahromi, Stachovych, and Ewing (2014) assert that customer retention should be accorded greater priority in B2B settings. This is particularly pertinent as customer retention has been shown to have a disproportionately significant positive impact on firm valuation (Gupta, Lehmann, & Stuart, 2004). With greater digitization, online and offline channels are increasingly merging in B2B sales systems. As Arli, Bauer, and Palmatier (2017) note, a large part of the sales process in B2B sales situations is now completed digitally, even before the first contact with a salesperson. With traditional models in flux, customer retention in B2B settings could well be increasingly challenging. In such a scenario, technological interventions in customer retention strategies could be a key differentiator.

Data mining and AI as opportunities

Customer retention strategies have been identified as a key area in marketing which have been impacted by technology (Kumar, 2015). Understanding customer retention as a phenomenon typically requires data over a period of time, related to many different aspects of the customer’s transactions (Kumar & Reinartz, 2016). As the authors note, ‘maximum likelihood estimation’ has been the preferred approach to model customer retention. However, with the growth of AI-related technologies, a promising avenue in implementing customer retention strategies is the use of sophisticated AI-based data mining applications (Jahromi, Stakhovych, & Ewing, 2014). It is important to note that predictive analytics, particularly in combating customer churn, has been touted as one of the most promising application areas of AI in marketing. However, choosing the right technology is often the trickiest bit.

As Ng and Liu (2000) assert, a guiding light in choosing the right technology, and to its application, is often domain knowledge and a deep understanding of the problem to be solved. Without the two in place, AI-based data mining applications, at the moment, are limited to being task solvers with little business import. An interesting application of AI-based data mining applications has been demonstrated in the area of customer churn analytics (Jahromi, Stakhovych, & Ewing, 2014). Here, the authors model predicted customer churn in a B2B context. Based on model predictions, high-profit customers who are the most vulnerable to potential churn are identified. Subsequently, through targeted customer retention messages, attempts are made to retain this highly profitable customer segment. Through the use of AI, this approach holds promise to target potential switchers, thereby avoiding blanket spending on customer retention, which has traditionally been the norm.

Summary

On the one hand, AI has been hailed as “the most important general-purpose technology of our era” (Brynjolfsson & Mcafee, 2017). On the other, the worth of customer retention as a business goal is being increasingly acknowledged. The challenge of using AI as a customer retention facilitator is an interesting one. The first steps in this direction are being taken in B2B settings. AI-based data mining applications have shown initial promise. With the availability of transaction data expected to increase exponentially, this data will serve as the training material for AI-based customer retention applications of the future. CMOs will be well-served to keep their antennas tuned to future opportunities!

 

References

  1. Arli, D., Bauer, C., & Palmatier, R. W. (2017). Relational selling: Past, present and future. Industrial Marketing Management.
  2. Brynjolfsson, E., & Mcafee, A. (2017). The business of artificial intelligence. Harvard Business Review.
  3. Doney, P. M., Barry, J. M., & Abratt, R. (2007). Trust determinants and outcomes in global B2B services. European Journal of Marketing, 41 (9/10), 1096-1116.
  4. Gupta, S., Lehmann, D. R., & Stuart, J. A. (2004). Valuing customers. Journal of Marketing Research, 41 (1), 7-18.
  5. Jahromi, A. T., Stakhovych, S., & Ewing, M. (2014). Managing B2B customer churn, retention and profitability. Industrial Marketing Management, 43 (7), 1258-1268.
  6. Kumar, V. (2015). Evolution of marketing as a discipline: What has happened and what to look out for. Journal of Marketing, 79 (1), 1-9.
  7. Kumar, V., Dixit, A., Javalgi, R. R. G., & Dass, M. (2016). Research framework, strategies, and applications of intelligent agent technologies (IATs) in marketing. Journal of the Academy of Marketing Science, 44 (1), 24-45.
  8. Kumar, V., & Reinartz, W. (2016). Creating enduring customer value. Journal of Marketing, 80 (6), 36-68.
  9. Ng, K., & Liu, H. (2000). Customer retention via data mining. Artificial Intelligence Review, 14 (6), 569-590.