MAM
Reviews and recommendations dominate 70% of shopping conversations on Twitter
Mumbai: Shopping is a hot topic in the social space, and especially so during the festive season in India. While shoppers turn to services like Twitter to discuss their big splurge plans, do these conversations about brands and products actually impact sales? With the festive season in full swing, microblogging platform Twitter’s latest #LetsTalkShop report finds out how marketers can engage the festive shopper more effectively.
Twitter partnered with Publicis to study 2,400 consumers in India on leading social platforms. The study reveals the sentiment that is driving conversations and shopping decisions today, while also throwing light on content consumption patterns and, most importantly, expectations from brands, both in terms of customer service and content.
Through these insights, Twitter has revealed how brand conversation powers shopping. Twitter wants to help marketers lean into shopping conversations and drive festive success this season.
Moreover, Diwali conversations on Twitter also open doors for Indian brands to connect and engage with the leaned-in shoppers who are looking to spend during the festivities. The service witnessed more than 3.1 million tweets about Diwali in the festive week (30 October 2021 to 6 November 2021).
As we head to the festive highs this year, Twitter India country lead-large client solutions, Kanika Mittal said, “Shopping has always been a social experience and the festive season is one of the busiest times of year on Twitter. Today, online brand conversation has become a trusted, everyday part of the shopping process. Our data reveals that 97 per cent of people surveyed seek comments and opinions from others on the service, with reviews and recommendations dominating 70 per cent of shopping conversations. Trust, too, plays a major role. 9 out of 10 consumers are more likely to consider a purchase after seeing someone else’s opinion about a brand or product. In fact, for the majority of shoppers, these spontaneous conversations are as impactful on purchase decisions as traditional reviews. So yes, talk matters.”
Reviews and recommendations on Twitter take a front-seat during festive shopping
Connecting with other shoppers to share experiences and make decisions based on these exchanges forms a significant part of today’s tech-savvy consumers’ purchase decisions. As a testament to this, the report indicates that 9 in 10 consumers are more likely to consider a purchase after seeing someone else’s opinion about a brand or product.
Reviews and recommendations dominate 70 per cent of shopping conversations on Twitter today. For consumers, Twitter has been one of the go-to services for them to help them in their purchase journey, as more than half (51 per cent) of Indian online shoppers agree that ads or tweets on Twitter help them discover new products or brands.
55 per cent state that reviews and comments on Twitter are more trustworthy than on any other social media platform.
Consumer Excitement And Buying Inclination During Diwali
The study reveals that the build-up to the festivities is the most exciting for consumers as 50 per cent of the Diwali conversation on Twitter takes place before the festival, whereas 35 per cent of the conversation happens on the day of the festival.
92 per cent of festive conversations around Diwali are mostly positive or neutral in tonality, with 75 per cent of mentions of Diwali on Twitter being linked to ‘joy’.
As brands increasingly tap into the power of click ‘play’ to engage with their audiences, the report notes that 64 per cent of people on Twitter enjoy watching video ads to see what brands have to offer.
Four in 10 shoppers are on the lookout for deals and promotional offers from brands around Diwali.
Brand conversations: A beaming opportunity for businesses
Brand conversation is increasingly becoming influential at every stage of the purchase journey and has the power to influence shopping decisions. As a matter of fact, 93 per cent of Indian shoppers recall brand conversations online before making a purchase.
In fact, shoppers on Twitter consider 4 out of 5 (80 per cent) of the brand conversations as “trustworthy.” 88 per cent of brand conversations made people feel differently about the brand. Among consumers that made a purchase, 62 per cent said that their experience with brand conversation made them much more likely to consider the purchase.
Evidently, consumers are increasingly seeking meaningful dialogue with brands. This festive season, engaging audiences beyond ‘clicks’ and moving towards ‘conversations’ is the route that brands must take to drive consideration and purchase behaviour.
Risk and return maintain inverse proportionality within mutual funds – higher potential rewards accompany elevated volatility, while stability demands lower expectations. SEBI’s Riskometer (1-5 scale) standardizes visualization, but quantitative metrics reveal nuanced relationships across categories and market cycles.
Fundamental Risk-Return Relationship
Equity funds (Riskometer 4-5) deliver historical 12-16% CAGR alongside 18-25% standard deviation—large-cap 15% volatility, small-cap 30%+. Debt funds (1-2) yield 6-8% with 2-6% volatility. Hybrids (3) average 9-12% returns, 10-14% volatility.
Sharpe ratio measures return per risk unit – equity 0.7-0.9, debt 0.5-0.7 over complete cycles. Higher risk categories compensate through return premium capturing economic growth.
Volatility Metrics Explained
Standard Deviation: Annual NAV return dispersion—equity 18-22%, debt 4-6%.
Maximum Drawdown: Peak-to-trough losses – equity 50%+ (2008), debt 8-12%.
Beta: Market sensitivity – equity 0.9-1.1, debt 0.1-0.3.
Sortino Ratio focuses downside volatility—equity 1.0-1.3 favoring recoveries.
Value at Risk (VaR) estimates 95% confidence, worst 1-month loss: equity 10-15%, debt 1-2%.
Category Risk-Return Profiles
Large-cap equity: 12-14% CAGR, 15% volatility, Sharpe 0.8.
Mid/small-cap: 15-18%, 22-30% volatility, Sharpe 0.7.
Corporate bond debt: 7-8%, 4% volatility, Sharpe 0.6.
Liquid funds: 6.5%, <1% volatility—capital preservation.
Credit risk debt: 8.5%, 6% volatility—yield pickup.
Hybrids: 10-12%, 12% volatility—balanced exposure.
Review types of mutual funds specifications confirming mandated asset allocations driving profiles.
Historical Risk-Return Tradeoffs (2000-2025)
Complete cycles: Equity 14% CAGR/18% volatility; 60/40 equity/debt 11%/11% volatility; debt 7.5%/5% volatility. Bull phases (2013-2021): equity 18%, debt 8%. Bear markets (2008, 2020): equity -50%/+80% swings, debt -10%/+10%.
Inflation-adjusted: Equity 8% real CAGR; debt 1.5% real—growth funding requires equity allocation.
Risk Capacity Assessment Framework
Short-term goals (1-3 years): Riskometer 1-2 (liquid/debt), 2-4% real returns. Medium-term (5-7 years): Level 3 (hybrid), 4-6% real. Long-term (10+ years): Level 4-5 (equity), 6-9% real.
Personal factors: Age (younger = higher risk), income stability, emergency fund coverage, other assets. Drawdown tolerance—20% comfortable vs 40% discomfort signals capacity limits.
Portfolio Construction Principles
Diversification: 60/40 equity/debt reduces volatility 40% versus equity-only while capturing 80% returns.
Correlation: Equity/debt 0.3 average enables smoothing.
Rebalancing: Annual drift correction sells outperformers (equity +25%), buys underperformers (debt -5%).
Style balance: Large-cap stability offsets mid-cap growth volatility.
Quantitative Risk Management Tools
Sharpe Ratio: >1.0 indicates efficient risk-taking.
Information Ratio: Alpha per tracking error.
Downside Deviation: Focuses losses only.
Stress Testing: 2008 scenario simulations reveal portfolio behavior extremes.
Conclusion
Higher mutual fund risk levels correlate with elevated return potential – equity 12-16% amid 18-25% volatility versus debt 6-8%/4-6%. Risk capacity matching, category diversification, rebalancing discipline, and quantitative metric interpretation align portfolios with personal tolerance across economic cycles.
Disclaimer: Investments in the securities market are subject to market risk, read all related documents carefully before investing.
