INTRODUCTION
The Bottom of the Pyramid (BoP), also referred to as the Base of the Pyramid, or the next billion customers, has caught the attention of many consumer packaged goods (CPG) companies, especially in the last decade. Prahlad and Hammond (2002) and Prahlad and Hart (2002) positioned the BoP population as a consuming class which is poor yet offers opportunities for high growth and profits to businesses. These consumers predominantly live in smaller towns and rural areas.
The BoP population was initially defined as people who live on less than $1 a day (World Bank reference). Another definition given the World Resource Institute (WRI) and the As per the estimates of the International Finance Corporation (IFC), base of the pyramid is defined using a cut off of USD 1.72 per person per day in the Indian context. However, this definition is not adequate to define the BoP as it considers only the income of an individual while neglecting other important aspects of poverty. A recent report by World Bank titled ‘Voices of the Poor’, states that the BoP description is multi-dimensional so it cannot be solely based on income levels and therefore it will consider factors such as lack of access to basic goods, services and economic opportunities. Thus the IFC elaborated the definition by including two more non-monetary aspects, namely, lack of basic goods and services and lack of income generation opportunities.
The business potential that exists in these segments is starting to interest businesses offering branded products because urban markets have become highly competitive for their brands (Burgess and Steenkamp, 2006).
However, lack of knowledge about brand value sought after by consumers and channel that caters to consumers in this segment dissuades suppliers of branded products to consider entering these markets. Supplier brands currently serving BoP consumers hesitate to directly approach retailers operating in rural markets and prefer to use alternative routes to address demand in this segment. Distributor companies as member of the business-to-business network of supplier’s brand facilitate availability of its products to consumers through local retailers operating in rural areas (Reinartz et al., 2011).
India has about 13 million stores, out of which 6 million stores deal in CPG. The share of modern and large stores is less than 10%. Some of the leading companies reach to about 5.5million of these stores. Only about 20% of these stores are service directly by the company through their field force. The rest 80% are covered indirectly through a long chain of distribution primarily controlled by wholesalers.
In many cases, customers face stock outs or higher prices. It is also found that the cost of serving these markets, especially in the rural India, is higher and in many cases manufacturers had to withdraw new product introductions. Therefore, manufacturers have found it a challenge to not only reach these outlets but also ensure the desired brand experience. The role of the village level retailer becomes important. This paper stresses on the importance of the role a retailer and attempts to examine how retailers serving the bottom of the pyramid markets adopt brands.
ADOPTION BY RETAILERS
Previous studies have been conducted to find out the factors that retailers consider while adopting new brands. However, given the importance of this phenomenon they are limited. The first study was published in Grahshof (1970) which addressed two primary decisions affecting the mix of products carried by a retail chain. These were related to (a) the addition of new items, and (2) the deletion of items now stocked by the chain. The main factors considered by a retailer for addition were demonstrated consumer demand, promotional programme of the suppliers, rate of movement, competitive reaction to the new item, test market information and the estimated sales as presented by the supplier. The most important criterion in the evaluation of an item being considered for deletion is its rate of sales, gross margin percentage of the item, the gross margin dollars earned, the item’s role in the mix of items carried by the chain and return on inventory investment. Heeler, Kearney and Mehaffey (1973) found a similar list of 13 items that affected the choice of a product by supermarket chains. They also found that these could be used in an additive or compensatory model. Montegomery (1975) added variables to the study related to category performance and shelf space utilisation.
There was long gap before studies started focussing on this phenomenon. In a study to understand the decision of a channel intermediary to add new products Rao and Mcluaghlin (1989) used a group of four variables of financial, competition, marketing strategy of vendors and category variables. Later White, Troy and Gerich(2000), Rao and Mahi (2003) and Lariviere and Padmanabhan (1997) studied the role of slotting fees and introductory allowances in the acceptance of new products. They found that these could be used to off- set the perceived risk of a new product. However, this effect was more pronounced in an interaction based model, indicating that these would become more effective in the presence of other variables such as manufacturer reputation, retail competition, and category sales volume. It is also noted that these variables are beyond the control of the manufacturers and hence difficult to manage. Hence retailers may not bring slotting fees and introductory allowances in choosing a product, but use it for increasing their revenues. Ailwadi (2001) found that trade promotions, consumer promotions and private brands were used by retailers and manufacturers to manage the balance of power between, though the effects might not always be in the desired direction. Retailers tend to adopt private labels to counter the manufacturers and increase profitability (Kumar and Steenkamp, 2007).
A shift in focus has been noted in the recent study in this regard. Researchers have started focussing on the relational aspect of the decision. Corsten, Daniel and Nirmalya Kumar (2005) explored the influence of collaborative efforts in adoption of Efficient Consumer response (ECR) by large retailers. They found that transaction-specific investments, cross- functional teams and incentive systems had a positive impact on adoption. The adoption had a positive effect on the supplier’s perceptual economic performance, archival sales and capability development.
Retailer capabilities have a positive effect on supplier perceptual economic performance, archival service performance and capability development. In a study of buyers’ selection of new products in grocery stores, Kaufman, Jaychandran and Rose (2006) demonstrate the role of firm–firm and buyer–salesperson relationships in retailers’ acceptance of new products. The findings indicated the increasing influence of buyer– salesperson and firm–firm relationships when a new product’s attractiveness is modest than when the new product is very unattractive or very attractive. In such a situation, the likelihood of new product acceptance could increase substantially based on a strong relationship of the buyer with the salesperson. A similar finding is reported in firm – firm relationship. Using trust, commitment and satisfaction, they infer that when the product is judged to be unambiguously weak or strong, buyers feel that the perceived risk could be reduced through relationship quality. Jap and Anderson (2007) studied the role of relationship length in adopting a new product. They indicated that goal congruence and information exchange norms change over the relationship lifecycle and the willingness to adopt new products may change with the length of the relationship. More recent literature (Dholakia et. al., 2012) emphasizes on the role of caste and family relationship within retail establishments and between wholesale and retail establishments hinting at the deep ethno- social fabric which plays an important role in business decision pertaining to procurement and credit policies. The study also makes a separate mention about the existence of ethnic- groups in the wholesale and retail trading communities in India, thus, signifying the possibility of the influence of caste in the procurement of goods.
In an ethnographic study of retailers, Varman and Costa (2009), illustrate that the ties among the retailing community are deep seated in the socio-economic framework which is an important tool that helps them grow and survive. Moreover, they also discovered that most permanent shops were simply an extension of the homes of the shopkeeper. Therefore, such literature accentuates the need to further explore and understand not only the role of retailers and trade partners but also that of the family in business decisions.
In a recent study, Everdingen et al (2011) used a combination of profit, category and relationship variables to understand product adoption by a chain of stores in Europe. They found that in each case, the relation with adoption in non-linear. A positive linear effect of the perceived new product uniqueness on a retailer’s utility to adopt has been found indicating that higher levels of uniqueness was associated with higher levels of retailer adoption probability. They also find that the relationship quality is not very significant. The expected category growth due to the new product introduction is positively associated with new product adoption as well as adoption by competing retailers. The probability of adopting a new product appears to be higher when a larger number of competing retailers has already adopted the new product. They also find that the adoption levels differ systematically between buyers and retail chains.
METHODOLOGY
Most studies in this area have used some of other type of models including simulation. They have used data from manufacturers as well as retailers. Most of these studies focus on the adoption by large retailers. The studies related to small retailers are limited and those relating to BoP retailers are scanty. Sixty retailers serving this population were selected. The cities in India possess mixed habitation. The customers belonging to different socio- economic strata live in the same locality. They also tend to buy from the same retailers. This is much more pronounced in food and grocery where Kiranas dominate. The share of new format self-service stores is still very low. The stores, therefore, were selected carefully so that these largely served the BoP customers.
METHOD
The purpose of the study was to develop a theory about the brand adoption behaviour of retailers serving the bottom of the pyramid market. Moreover, in order to ensure all possible existing themes were captured, the study was specifically designed to be open- ended. A discussion guide was prepared that contained broad questions about how BoP retailers adopted brands.
Villages in 4 districts of the Indian state of Gujarat were selected to represent the BoP customers. In-depth interviews were conducted with 60 retailers from 28 villages belonging to these districts. These retailers were a suitable group because they served a population, which did not have high-income sources. Majority of the people in the villages worked in the agriculture sector and some others worked as daily labourers in nearby Talukas1. Moreover, the population of these villages had no or limited access to basic facilities likes healthcare, education and sanitation. Therefore, as per the definition of BoP by IFC, most of the findings reflected the existence of BoP population in these villages. The survey was conducted in villages where the population ranged from 834 to 30871. The population of only 3 villages were in excess of 5000. A total of 7 retailers were covered from these 3 villages but these retailers were located in the peripheral areas and away from main the village, where these retailers sold goods only to BoP consumers, primarily contractual labourers at construction sites. Some of the villages had primary schools. The population of some of the villages had access to a clinic in the village, while others were required to visit the nearest Taluka for medical help. All the 60 shopkeepers who were interviewed were males. The average size of the store was approximately 100 square feet with the smallest store measuring about 30 square feet and the largest measuring about 250 square feet in size. Each village had multiple shops which were generally located in different parts of the village and served a faintly distinct area. The villages did not have defined areas like markets, roads, and parks. In most of the cases the shops were located with the villagers’ residences.
The retailers sold a wide range of products, FMCG, cereals, vegetables, footwear, stationery, tobacco products, electronic items and mobile recharge coupons. Majority of the income of these retailers came from processed and raw food items. Some of them also sold electronic goods like batteries and torches and flashlights.
All the interviews were conducted in person and at the retailer’s shop mostly in the afternoon when they were to participate in the discussion. The retailers were interviewed only if they gave their consent to be a part of the study and those who were reluctant were not interviewed. The retailers were informed that the objective of the study was to understand how retailers decide which brands to select or reject and the reasoning behind such a decision. No systematic differences in the quality of data or in the substance of interviews conducted in different ways was detected. Wherever required they were asked to cite examples and cases to bring out the dimensions. The average length of interviews was 24 minutes, the longest one lasting for 88 minutes. The interviews were audio-recorded and they yielded about 400 pages of transcript.
| Number of samples | Village | Taluka | District | Population2 |
| 2 | Shrinagar | Sanand | Ahmedabad | 600-650* |
| 1 | Kodaliya | Sanand | Ahmedabad | 834 |
| 2 | Gokulpura | Sanand | Ahmedabad | 1000-1500* |
| 1 | Khicha | Sanand | Ahmedabad | 1883 |
| 3 | Lekhamba | Sanand | Ahmedabad | 1356 |
| 1 | Fangdi | Sanand | Ahmedabad | 2430 |
| 1 | Goraj | Sanand | Ahmedabad | 4242 |
| 3 | Bareja | Daskroi | Ahmedabad | 15427 |
| 1 | Bavla | Daskroi | Ahmedabad | 30871 |
| 2 | Khodiyar | Daskroi | Ahmedabad | 2915 |
_______________
* Population of these villages was taken as mentioned by the retailers2 Data taken from Census 2011, Government of India (Ministry of Home Affairs) – http://censusindia.gov.in/PopulationFinder/Population_Finder.aspx [Accessed on 13th March, 2014]
| 3 | Shilaj | Daskroi | Ahmedabad | 4341 |
| 1 | Bhadaj | Daskroi | Ahmedabad | 2281 |
| 1 | Lilapur | Daskroi | Ahmedabad | 1231 |
| 3 | Rajoda | Bavla | Ahmedabad | 3392 |
| 1 | Rasam | Bavla | Ahmedabad | 2761 |
| 3 | Dhanaj | Kalol | Gandhinagar | 2259 |
| 1 | Palsana | Kalol | Gandhinagar | 3691 |
| 2 | Jaspur | Kalol | Gandhinagar | 2934 |
| 2 | Rancharda | Kalol | Gandhinagar | 2770 |
| 2 | Jank | Gandhinagar | Gandhinagar | 1000-1500* |
| 1 | Panchha | Danta | Banaskantha | 1306 |
| 3 | Danta | Danta | Banaskantha | 6753 |
| 5 | Koteshwar | Danta | Banaskantha | 1126 |
| 2 | Chikhla | Danta | Banaskantha | 1172 |
| 1 | Baga | Danta | Banaskantha | 1000-1500* |
| 6 | Hadad | Danta | Banaskantha | 3144 |
| 3 | Kheroj | Khedbrahma | Sabarkantha | 1014 |
| 3 | Jetalpur | Mehsana | Mehsana | 1331 |
Table 1: List of villages covered in the study
ANALYSIS
The transcripts were subjected to grounded theory based analysis (Glaser and Strauss, 1967). Three independent investigators read the transcripts. They conducted open coding these transcripts which generated 533 general descriptions of brand selection criteria employed by the retailers. The emerging codes were also searched through previous literature on the subject in order to identify whether the codes could be related with any theme from the relevant literature. Thereafter a round of axial coding (Strauss and Corbin, 1998) was conducted to sort the descriptions into 99 sub-themes. The available 99 were further analysed to create 15 concepts that described the major themes as emerging from the interviews. The details of the emerged sub-themes, concepts and the categories have been shared in Annexure A. These concepts were then further classified into 4 categories that served as the major constructs of the BoP retailers’ brand adoption criteria.
FINDINGS
BRAND RELATED FACTORS
BRAND AWARENESS
“The brands which are advertised on TV or newspaper generally sell more than the non-advertised brands. When a vendor comes and shows his new brands and I reckon having seen it on TV, I will keep it in my shop.”
Stocking well-known and established brands was universal. All retailers would stock these brands as customers would ask for such brands and would leave without purchasing if the desired brand was not available. These retailers considered advertised brands as established brands and were only interested in stocking them. These retailers stocked only known brands because they believed that advertised brands had better product quality as compared to non-advertised brands and for these retailers product quality was an important driver of sales. They did not differentiate between national or local or MNC brands.
However, it was observed that all retailers also stocked lesser known brands in the same product category. One of the primary reasons of retailers in stocking lesser known brands was that these brands offered higher sales margins than known brands. The known brands sold in larger quantities but offered lesser margins. Therefore, by stocking both known and other brands retailers increased their overall profit as also served to a wider segment of customers. The other motivation to select lesser known brands was that these brands were available on credit, unlike the established brands.
“Yes, I will keep it. There are many national political parties but that doesn’t mean regional parties will not emerge. So many major and reputed brands like
Many retailers shared that when they come across a brand which they were not aware but it enjoyed clear demand in some other market, they would be very interested in stocking that brand. At the same time, few retailers also mentioned that they would not be willing to stock the products of a brand, whose name they have never heard before. Thus, highlighting that minimal brand awareness was an important pre-requisite before finalizing the brand. Very few retailers were reluctant to stock brands whose names they have never heard of.
BRAND PROMOTIONS
“Once a company gave me an offer that when I purchased 5-6 boxes of its product, they will give me 2 more free boxes. But at that time I said that I don’t want any type of offer or any extra boxes. If your product sells then you will get the money, If it doesn’t…”
At the distribution level, retailers and other channel partners are often given extra stock on the purchase of a minimum quantity. This would essentially increase the retailer’s profit margin and turnover. However, the BoP retailers were divided in their opinion.
“I want to look for profits but these companies play tricks. Earlier this 100 gram packet of biscuit was sold at Rs 5. In recent times the brand reduced the quantity to 60 grams and now they have decreased the quantity further. But the price remains the same. So I can’t earn enough margins”
About half of the retailers interviewed were not particularly motivated to select a brand just because they have a launch scheme or discount to offer. Although the promotional offers influenced the retailer’s purchase decision but it did not do so as a standalone factor. For these set of retailers, other aspects of selection process, for instance, customer demand, were more important than discounts. Retailers were interested in adopting a brand if it was sold and not because the brand or supplier was offering free boxes with a purchase. Their primary apprehension was that under the pretext of discounts and freebies brands would dump their stock at their shops and in case if that stock is not sold then they will have to suffer huge losses. Such a scenario would completely reverse the underlying objective with which the retailers had purchased the stock. Other forms of brand promotions, such as television advertisement, newspapers advertisement and others, did not motivate all of them to adopt brands. The retailers’ reasoning was that such forms of marketing work only in urban centres where the customers are educated and that in their rural areas such promotions did not help them increase sales. This brings out an important point that the retailers considered brand promotion as a determinant in selecting brands only when brand promotions were effective in reaching the consumers and in increasing sales.
“Mostly for any new brand they give 30-40% margin otherwise they give free packet, meaning if I buy defined stock quantity I get 5 packets free and other such schemes. Established brands do not offer that much profit. Take the example of
About half of the retailers have also shared that brand promotions influenced their decision making process and the reason understood is two-fold. Firstly, promotions involving discounts and schemes were welcomed by a lot of retailers as they help the retailer to increase his/her overall profit margin. Since the turnover of BoP retailers has been found to be less compared to their urban counterparts, BoP retailers have shown an inclination to adopt brands that help them increase overall profit margins. For example, providing retailers free units of a product on purchase of a minimum quantity will increase the average margin per unit of the total purchase. And secondly, promotional schemes for customers, such as buy-one-get-one-free, also positively influence the retailers’ decision as they feel that such offers will motivate customers to buy the product and thus increase the retailers’ sales.
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