Social Media as a Tool for Social Commerce: A Content Analysis of Women Entrepreneurs in Haryana

Introduction

Women's role in social and economic development of India has always been pivotal and entrepreneurship is one of the most direct means by which women's contribution is manifesting economic independence. The Sixth Economic Census, published by the Government of India, Ministry of Statistics and Programme Implementation places the ownership of Women at around 14% of the total 58.5 million business establishments in the country, with about 8.05 million business establishments and over 13 million employment [1]. In this context, social media has become one of the most cost-effective and accessible marketing platforms for women entrepreneurs, including those who do not have formal business structures, to promote products, establish a customer base and create a brand for their businesses without the need for retail outlets and significant investment.In this background, social media is one of the most cost-effective and accessible market channels for women entrepreneurs, especially those without formal business infrastructures, to promote products, target customers and build a brand without relying on retail outlets or high capital expenditure [2]. This change is especially notable in semi-urban and rural areas—like Haryana, where women's involvement in formal commerce has always been limited due to the constraints of mobility and the lack of access to credit facilities and social norms around women's role in trade.

While there is evidence that social media is facilitating women entrepreneurs by making it easier to be an entrepreneur, to the best of the author's knowledge, little work has focused on the actual practice of women entrepreneurs on social media in India – specifically, the platforms they use, how they cultivate their platforms, what types of content they post, and how they create and maintain customer relationships in a local language. This study addresses that gap through a quantitative content analysis of ten women-run YouTube channels in Haryana selling clothing and related products, coded across twenty-two variables covering platform choice, channel growth, posting behaviour, and customer engagement.

The specific objectives of the study are to:

• analyse the various social media platforms used by women entrepreneurs to grow their business;

• examine growth and audience participation in women entrepreneurs' businesses through social media;

• find out the change in the self-presentation and content behaviour of women entrepreneurs across the platforms they use; and

• analyse how women entrepreneurs build relationships with customers through social media and how these relationships are maintained.

The contribution of this paper is twofold. Academically, it provides a platform-level, coded content analysis of women's social commerce behaviour in a specific regional Indian context, addressing a gap left by broader survey-based studies of women's social media adoption [2]. Practically, its findings are intended to inform digital-literacy and skill-training programmes aimed at rural and semi-urban women entrepreneurs, given that the Sixth Economic Census shows the large majority of women-owned Indian enterprises remain small and self-financed [1]; policymakers and non-governmental organisations designing such programmes can use the platform- and behaviour-level patterns identified here to target training more precisely, for instance toward cybersecurity awareness, where this study finds a persistent gap. The remainder of the paper is organised as follows: Section 2 reviews related literature and sets out the theoretical framework; Section 3 describes the methodology; Section 4 presents the results; Section 5 discusses the findings; and Section 6 concludes with implications and directions for future research.

Literature Review

Social Media and Women's Entrepreneurial Capability

There is emerging evidence of the changes social media platforms are bringing to the ways women are entering and operating in business. Similarly, social media has also been associated with entrepreneurial opportunity for women, in that they require limited capital and infrastructure to start and operate a business, as stated by Hossain and Rahman [3] and Goswami and Dutta [4] who have applied the UTAUT model to reveal that performance expectancy and facilitating conditions are found to be important predictors of the adoption of e-commerce tools among women entrepreneurs in India. In a similar vein, Ukpere, Slabbert, and Ukpere [5] find that the proliferation of social media has opened up business opportunities for women entrepreneurs in various national settings and contexts. In the study by Al Omoush [2] on women's adoption of social commerce businesses, perceived value, social commerce literacy, entrepreneurial mindset and collaborative ecosystems were found to be important predictors of successful adoption, while at the same time, successful adoption enhanced the overall entrepreneurial position of women. Combining these studies, it can be concluded that platform adoption is not just a technical decision; it is tied to the confidence of the users and their competency in using the tools, all of which are pertinent to the platform-choice patterns explored in the present study.

Social Commerce Adoption Among Small Entrepreneurs

Research on social commerce adoption by SMEs confirms this scenario. In their study of 105 Malaysian entrepreneurs, Hashim, Nor and Janor [6] observed that social media was widely used as a commercial vehicle that required little investment as it enabled the low barrier of communication directly with a huge population of potential buyers, however, awareness of the real potential of s-commerce was still uneven. Also, in the studies that Theis and Rusconi reported, Women's World Banking surveyed women entrepreneurs in India and Indonesia, and they reported that women often used Facebook in combination with WhatsApp or Instagram, not only to market products but also to engage in a regular stream of communication with repeat customers -- a trend that is similar to the channel-combination that occurred for the channels sampled in this study.

Financial and Digital Literacy in Women's Digital Commerce

Women's digital commerce has also been a constant focus of the financial and infrastructure environment has also been under constant discussion. Peter et al. [8] surveyed 214 women entrepreneurs in India and concluded that the entrepreneurial digital financial literacy played a significant role in predicting financial inclusion and firm performance, indicating that digital platform usage is not sufficient for business growth without financial and digital skills. This is in line with the Sixth Economic Census result that most women entrepreneurs are in small units and they use either their own capital or other sources of finance, with the overwhelming majority being self-financed and own-account units in India [1].

Risks of Online Visibility for Women Entrepreneurs

There is a body of literature that talks about the dangers of this chance. In a systematic review of 31 studies on cyberbullying against women, Gallegos et al. [9] identified that the most common types of cyberbullying experienced by women were online harassment and threats, which were found to occur mostly on social media and message platforms and to have documented impacts on the mental health of victims. Women entrepreneurs who establish an online business that is visible to the public are not immune to this risk and, as the results of this study indicate, several of the channels sampled seem to have an incomplete understanding of cyber security and privacy protection based on their level of visibility to the public online.

Relationship-Building and Language in Social Commerce

Previous research on social commerce for relationship marketing indicates that platform selection is not as important as language and local-community framing. Suganya and Thenmozhi [10] suggest that one of the main drivers where small women business owners register customers without brand recall is trust building, which is directly explored in this study by the language that the channels used (Haryanvi vs Hindi).

Theoretical Framework

The areas of the study are approached with a different well-defined theoretical perspective for each objective. The platform selection (Objective 1) is addressed by the theory of uses and gratifications [11] which states that users actively choose media channels that most effectively meet their social and informational needs, in this case low-cost, mass media and visually-appealing product promotion. Channel growth and participation (Objective 2) is addressed using Social Capital Theory [12] which considers audience growth (subscribers, views, engagement) as a building or accumulation of social capital within a network, which can be converted into economic opportunity. Objective 3 addresses Change in entrepreneurs' presentation style and content behaviour across platforms (Objective 3) using the theory of self-presentation developed by Goffman [13] that posits that the presentation of contents in the public sphere is a performance that is managed with the aim of projecting a specific and credible business identity to an audience. Lastly, Customer-Relationship Building (Objective 4) is done using Relationship Marketing Theory [14] which states that customer success is more about long-term, secure, and trusted relationships with customers than individual transactions. When these frameworks are combined, the bottom line is that women entrepreneurs who most optimally align their choice of platform to their audience needs, have a high level of control over their public self-presentation and engage with relationship-building communication will exhibit proportionately greater channel growth. As a whole, this literature indicates that women's access to social media reduces the barriers to women entrepreneurship; that financial and digital literacy influences the benefits to be gained from this access; and that the visibility of women on social media is not equally distributed by gender. It has not generated a platform-level content analysis of how the women entrepreneurs in the specific Indian context of rural and semi-urban Haryana are really operating on platforms – which platforms they use, how their channels develop, what they post, and how they cultivate their customer base in a local language. This study aims to fill this gap.

Methodology

Research methodology is a sequence of procedures followed to find, select, process and analyse information regarding a research topic [15]. The quantitative technique content analysis is used in this study to analyze social media usage by women entrepreneurs. In the methodological literature several complementary definitions of content analysis have been provided, such as: content analysis is the objective, systematic and quantitative description of the manifest content of communication [16]; content analysis is a systematic, objective and quantitative study of communication which measures variables [17]; content analysis is a set of procedures used to make inferences from text in a valid manner [18]; and content analysis is any technique used to make inferences about the text in an objective and systematic and quantitative manner [19].

Research Design

This study follows a descriptive, quantitative content-analysis design, applying a structured coding instrument to social media posts in order to describe patterns of platform use, growth, and engagement rather than to test causal relationships between variables.

Population and Sample

The target population of the present study is the women entrepreneurs in online business in haryana. A list of such entrepreneurs was obtained by initially finding a sampling frame comprising 30 women owned YouTube channels selling clothing and related products, based in the state of Haryana, whose number of subscribers, number of handles and the date of channel creation were recorded. The ten channels with the highest number of subscribers were chosen as channels for detailed coding from this frame (Table 1). The other 20 channels, which had between about 2000 and 75000 subscribers, were not coded in detail, but provide confirmation that the 10 chosen for detailed coding are generally representative of the channels of similar women entrepreneurs in the Haryana area, and not uncommon or outlying cases.

Table 1. The Ten Sampled Channels (Ranked by Subscriber Base)

Sampling Technique

The study uses convenience sampling, a non-probability method in which units are selected based on accessibility to the researcher [15]. This technique was chosen because no complete, verifiable list of women entrepreneurs conducting business on social media in Haryana currently exists; the researchers therefore built the sampling frame directly through platform search and identified the ten most-subscribed clothing-business channels meeting the inclusion criteria (Haryana-based, women-led, actively posting business content) as the coded sample. A sample of ten channels, yielding 290 individually coded posts, is consistent with prior small-sample content-analysis designs of regional micro-entrepreneurship [6] and allows for detailed, post-level coding rather than shallow, channel-level description alone.

Instrument and Coding Categories

A structured codebook of twenty-two variables was developed to code each sampled post and channel: channel name; type of comment received; total comments on the post; time of live broadcast, if any; number of posts shared per day; type of content used for the post (live, recorded, reel, story); type of post (business, blog, personal story); total likes on the post; total views on the post; advertisements appearing in the video; discounts offered; delivery charges; sector of business; location of business (urban, rural, town); total channel subscribers; years active on the platform; total videos uploaded; total channel views; language used; type of channel disclosure (membership, branch details, sentiment-based); gender of the presenter; and type of media platform used for business. The full coding instrument, with category definitions, is provided in Appendix A to support replication.

Data Collection and Reference Period

The ten sampled channels were established between December 2012 and August 2022, and coding was carried out on each channel's active post history as of the 2024-25 academic data-collection period. The exact start and end dates of the 290-post coding window were not separately recorded in the original coding sheet; this is acknowledged as a limitation in Section 5.6 rather than an exact window being invented here. This is a content-analysis study with two nested units of analysis: the individual social media post (N = 290) is the primary unit for post-level variables (comment type, content type, likes, views, advertisements, discounts, delivery charges), while the individual channel (N = 10) is the unit of analysis for channel-level variables (subscriber count, years active, total videos, business sector, location, and language).

Data Analysis and Statistical Techniques

Coded data were analysed using descriptive statistics -- frequency counts and percentages -- for each of the twenty-two variables, calculated as (frequency of category / total valid responses) x 100%. Cross-tabulations were used to examine any category showing an unusually high or low percentage relative to its comparison group within the same table. Data coding was carried out using a structured codesheet, with frequency and percentage analysis and chart generation performed in SPSS and Microsoft Excel.

Reliability and Validity

Content validity was supported by grounding the twenty-two coding categories in constructs established in prior social-commerce and content-analysis literature [2], [6], [16]-[19]. All coding was carried out by a single coder, and no formal inter-coder reliability statistic (such as Cohen's kappa or Krippendorff's alpha) was calculated; this limits the ability to rule out coder subjectivity in categories such as comment sentiment and is addressed further in Section 5.6.

Ethical Considerations

All data coded in this study were drawn from publicly accessible YouTube channels and posts; no private accounts, direct messages, or non-public content were accessed, and no direct contact was made with channel owners or viewers. Because the channels analysed are commercial, public-facing business accounts rather than private individuals, channel names are reported openly in Table 1 in the same manner as prior published content-analysis studies of public social media accounts. No personally identifying information about private individuals commenting on the sampled posts was recorded or reported; only aggregate, category-level comment data were coded.

Results

This section reports the descriptive findings of the content analysis objectively, organised by the study's four objectives; interpretation of these findings in relation to theory and prior literature is presented in Section 5. All ten channels operate in the clothing sector (100%), reflecting the composition of the sampling frame. Business location was evenly split between urban and village settings (40% each), with the remaining 20% based in small towns (kasbas). All ten channels (100%) were presented by women, consistent with the study's sampling criteria. Channel disclosure practices varied: 40% of channels shared other identifying details not captured by the remaining categories, 20% disclosed branch information, 20% conveyed a sentiment-based description, 10% disclosed membership information, and 10% disclosed none of these. Time active on the platform showed no consistent pattern: channels active for 1-3 years, 3-6 years, and 6-9 years were each equally represented (20%), while 40% fell into other duration bands.

Platform and Language Use

Table 2. Platform and Language Used for Business Promotion (N = 10 Channels)

Table 2 shows that YouTube was used, either alone or in combination with another platform, by all ten sampled channels, and was the sole platform for 70% of them. The remaining channels supplemented YouTube with Instagram (20%) or Facebook (10%) rather than replacing it. Sixty per cent of channels communicated primarily in Haryanvi rather than standard Hindi.

Channel Growth and Audience Participation

Table 3. Channel-Level Growth Indicators (N = 10 Channels)

Table 4. Post-Level Engagement Indicators (N = 290 Posts)

Sixty per cent of channels reached subscriber bases between 1 lakh and 50 lakh, and 80% reached cumulative channel views between 1 crore and 10 crore (Table 3). The channel tier with the highest video count (1,500-2,000 videos, 50% of channels) did not correspond one-to-one with the highest subscriber tier. Per-post views, likes, and comments were concentrated in mid-range bands: 50.3% of posts received 10,000-100,000 views, 50.0% received 1-500 likes, and 73.1% received 1-50 comments (Table 4).

Self-Presentation and Content Behaviour

Table 5. Posting Behaviour and Content Type (N = 290 Posts)

Recorded content (60.0%) was used more than live broadcasting (22.4%), and 59.7% of posts involved no live broadcasting at all; where live sessions did occur, no single time slot dominated. Business-oriented content accounted for 79.7% of posts, compared with 1.7% blog-style and 1.0% other content (Table 5).

Customer Engagement and Commercial Practices

Table 6. Customer Engagement and Commercial Practices (N = 290 Posts)

Positive comments (34.1%) far outweighed negative comments (0.7%), and posts drawing a mix of comment types were the single largest category (38.3%). The majority of channels (58.5%, combining the "special occasions," "festivals," "weekend," "daily," and "all of the above" categories) offered some form of periodic discount, and 46.5% did not charge delivery fees (Table 6).

Composite Summary Across Objectives

Table 7. Composite Summary of Headline Indicators Across the Four Objectives

Fig. 1. Composite Summary of Headline Indicators Across the Four Objectives.

Discussion

Platform Choice and Uses and Gratifications Theory

YouTube's use by all ten sampled channels, and as the sole platform for 70% of them, strongly supports Hypothesis 1 and is consistent with Uses and Gratifications Theory [11]: for entrepreneurs selling clothing, where visual demonstration of fabric, fit, and styling is central to the sales pitch, YouTube's long-form video format best satisfies the specific gratification these entrepreneurs are seeking -- richer product demonstration than static-image platforms allow. The remaining channels supplemented YouTube with Instagram or Facebook rather than replacing it, indicating that video remains the anchor platform even where a second channel is added for reach. That 60% of channels communicated primarily in Haryanvi rather than standard Hindi supports the relationship-marketing expectation [14] that small entrepreneurs build trust through language that signals shared regional and community identity to their local customer base, consistent with Suganya and Thenmozhi's [10] observation that community-specific communication substitutes for formal brand recognition among small women-led enterprises. In answer to RQ1 (which platforms women entrepreneurs predominantly use), the data show YouTube is unambiguously dominant, used either alone (70%) or combined with Instagram (20%) or Facebook (10%), with Haryanvi the primary promotional language for 60% of channels.

Channel Growth and Social Capital

Substantial audience accumulation -- 60% of channels reaching 1 lakh to 50 lakh subscribers and 80% reaching 1 crore to 10 crore cumulative views -- is direct evidence of the network-based social capital described by Coleman [12], accumulated by entrepreneurs operating without formal marketing infrastructure. Notably, the channel tier with the highest video count did not correspond one-to-one with the highest subscriber tier, and per-post views, likes, and comments were concentrated in mid-range bands rather than scaling in direct proportion to posting volume. This supports Hypothesis 2's expectation that growth does not track posting frequency in a simple linear way: audience accumulation on these channels appears driven more by cumulative reputation and word-of-mouth network effects than by the sheer quantity of content published. In answer to RQ2 (the extent of audience growth and participation), growth is strong overall but not linearly tied to posting volume.

Self-Presentation and Content Behaviour

Read through Goffman's [13] theory of self-presentation, the dominance of recorded content (60.0%) over live broadcasting (22.4%), and of business-oriented posts (79.7%) over personal or blog content, indicates that these entrepreneurs manage a fairly consistent, business-first public persona rather than blending personal-life content with commercial content -- supporting Hypothesis 3. The reliance on recorded rather than live content also suggests a preference for a more curated, editable self-presentation over the less-controllable, real-time format of live broadcasting; where live sessions did occur, no single time slot dominated, suggesting entrepreneurs use live formats opportunistically rather than on a fixed publishing schedule. In answer to RQ3 (how self-presentation and content behaviour vary across platforms), the pattern is one of a managed, business-first identity built predominantly on recorded content.

Customer Relationships and Relationship Marketing

The dominance of positive comments (34.1%) over negative comments (0.7%), and the prevalence of posts drawing a mix of comment types (38.3%), suggest these channels function as genuine two-way engagement spaces rather than one-directional advertising. Consistent with Relationship Marketing Theory [14], which holds that sustained success depends on ongoing trust-based interaction rather than one-off transactions, the majority of channels (58.5%) offered some form of periodic discount, and nearly half (46.5%) did not charge delivery fees -- both practical, low-cost relationship-sustaining gestures aimed at a repeat local customer base rather than one-time buyers. This pattern supports Hypothesis 4: responsive engagement, occasional discounting, and low-friction delivery terms, combined with the local-language communication discussed in Section 5.1, together form the primary mechanism by which these entrepreneurs build and retain customer relationships. In answer to RQ4 (how entrepreneurs build and sustain customer relationships), relationship-building rests on responsive engagement and low-friction, locally-anchored commercial terms rather than aggressive advertising alone.

Overall Synthesis

Read together, the composite pattern across all four objectives (Table 7, Fig. 1) is internally consistent: entrepreneurs who concentrate on a single, visually rich platform (YouTube), post predominantly business-first recorded content, and combine that with locally-anchored, responsive customer engagement are the ones who accumulate the largest audiences. This is broadly consistent with the overall theoretical expectation set out in Section 2.6 -- that platform-audience fit, managed self-presentation, and relationship-building communication together drive channel growth -- though, as discussed in Section 5.2, the relationship is not strictly linear with respect to posting volume alone. Across all four hypotheses, the pattern that emerges is one of concentrated, strategic platform use: rather than spreading effort thinly across many platforms, the women entrepreneurs in this sample concentrate on one visually rich, video-first platform, present a consistent business-oriented identity on it, and use low-cost relational tools -- language, responsiveness, discounts -- to convert audience attention into repeat local custom. This is broadly consistent with, and extends to a platform-behaviour level, the adoption-level findings of Al Omoush [2] and the channel-combination patterns reported by Theis and Rusconi [7]. At the same time, none of the channels examined showed evidence of structured digital-literacy or cybersecurity training, despite operating public-facing commercial identities that, per the wider literature on online harassment [9], place them at meaningfully elevated risk of online abuse relative to private social media users -- a gap these entrepreneurs appear to be navigating largely on their own.

Limitations

Limitations refer to the constraints on a study's design or conduct that may affect the interpretation or generalisability of its findings [15]. First, the sample is confined to ten channels within a single business sector (clothing) in one Indian state, selected through convenience sampling; findings should not be generalised to women entrepreneurs in other sectors or regions without further study. Second, as noted in Section 3.7, all coding was carried out by a single coder with no formal inter-coder reliability statistic reported, which limits the ability to rule out coder subjectivity in categories such as comment sentiment. Third, the composite summary presented in Table 7 is a descriptive heuristic -- a simple aggregation of already-reported percentages -- and not a statistically validated scale. Fourth, this study analyses manifest, publicly visible content (posts, comments, subscriber counts) rather than entrepreneurs' or customers' actual lived experiences, motivations, or psychological responses; pairing this content analysis with audience or entrepreneur interviews would be a valuable direction for future research. Finally, the exact start and end dates of the 290-post coding window were not recorded in the original data-collection instrument, so the reference period reported in Section 3.5 is described at the level of channel-creation dates and the general data-collection period rather than as a precise date range.

Conclusion

This study set out to examine how women entrepreneurs in Haryana use social media to conduct social commerce. The evidence points to a consistent and coherent pattern: these entrepreneurs concentrate their efforts on a single, visually rich, video-first platform -- overwhelmingly YouTube -- rather than spreading their presence thinly across many channels; they maintain a business-first public identity built on recorded rather than live content; and they sustain their customer base through responsive, positively-toned engagement conducted substantially in the local Haryanvi language, backed by low-friction commercial practices such as periodic discounting and, in many cases, free delivery. Social media in this context functions less as a marketing add-on and more as the primary infrastructure of the business itself, allowing women with limited access to formal capital, retail space, or institutional credit -- a constraint documented at national scale by the Sixth Economic Census [1] -- to build a functioning, audience-backed enterprise from home.

The main practical implication is that policy and programme support for women's social commerce in regions like Haryana should move beyond simple digital access and toward targeted digital-literacy, financial-literacy, and cybersecurity training, since this growth is currently occurring without commensurate formal support. Future research should extend this platform-level content analysis to other business sectors and Indian states, incorporate inter-coder reliability testing, and pair the manifest content coded here with interviews or surveys of entrepreneurs and customers to capture the motivations and lived experience behind the patterns identified.

Acknowledgements

The authors thank the administrators of the sampled YouTube channels for making their business content publicly accessible for academic analysis.

Funding

This research received no external funding.

Conflict of Interest

The authors declare no conflict of interest.

Data Availability Statement

The coded dataset (channel-level and post-level frequency data across the twenty-two coding variables described in Section 3.4) is available from the corresponding author upon reasonable request. The ten sampled YouTube channels are publicly identified in Table 1 and their content is publicly accessible on YouTube.

AI Usage Disclosure

A generative AI writing assistant or AI tool was not used to collect, code, or analyse study data, and did not generate the study's findings or interpretations, which remain the responsibility of the authors. The AI tool is not listed as an author and had no role in the conceptualisation of the research.

Author Contributions

Author contributions are reported using the CRediT taxonomy. Kusham Lata: Conceptualization, Methodology, Supervision, Writing - Review & Editing. Nisha: Investigation, Data Curation, Formal Analysis, Writing - Original Draft. Both authors reviewed and approved the final manuscript.

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Appendix A. Coding Instrument

The following twenty-two variables constituted the structured coding instrument applied to each sampled post and channel (Section 3.4), provided here in full to support replication.

Channel name

Type of comment received (none, positive, negative, advice, mixed, other)

Total comments on the post

Time of live broadcast, if any

Number of posts shared per day

Type of content used for the post (live, recorded, reel, story)

Type of post (business, blog, personal story)

Total likes on the post

Total views on the post

Advertisements appearing in the video

Discounts offered

Delivery charges

Sector of business

Location of business (urban, rural, town)

Total channel subscribers

Years active on the platform

Total videos uploaded

Total channel views

Language used

Type of channel disclosure (membership, branch details, sentiment-based)

Gender of the presenter

Type of media platform used for business