Marketing Spends Are Quickly Moving To The Developing Economies

The lure of huge online audiences, data-driven metrics, and higher returns on investment has accelerated the migration of marketing dollars from old media to new. The largest global marketers are ramping up spending, drawn by the huge potential opportunities offered by rapidly expanding wealth in the developing world. Yet the benefits of globalized marketing mask enormous hidden costs and risks: marketers are accelerating investments in economies where they typically have only a modest ability to track and assess results or optimize their return on marketing investment (ROMI). As these multinational companies throttle forward, they risk stalling instead, wasting millions of dollars on ineffective marketing initiatives. More crucially, they are jeopardizing their hard-won momentum in gaining competitive advantage in the economies now driving global growth.

There is a better way. Based on our experience in many countries, including Brazil, China, India, Russia, and Vietnam, we have identified five practical steps that marketers can take to jump-start their ability to measure marketing effectiveness in RDEs.

Media spending alone in developing economies increased by up to $60 billion from 2007 through 2012. Total digital-media spending worldwide, meanwhile, rose by about $55 billion. While some of the increased spending in emerging economies includes digital media, much of it is flowing to traditional media, such as television, magazines, newspaper, radio, and outdoor advertising.

Many large companies today spend more on just the advertising portion of their overall marketing budgets than they do on capital investment—often deploying far less analytical rigor in tracking the return on investment. Among a sample of more than 150 Fortune 500 companies that publicly report their advertising expenses, nearly a third devoted as much to advertising as to capital expenditures. Nearly half reported that their advertising expenses rose faster than capital investments over the preceding five years.

One of the world’s 100 largest brands found that the return in its best market was 27 times better than in its worst. Even in well-developed, data-rich markets like Japan, the U.S., and Western Europe, many companies are still frustrated by their inability to measure and optimize marketing performance. Difficulties are often compounded in developing markets, where the challenges can include the following:

• Lack of accurate sales volumes and point-of-sale transaction data
  
• Absence of accurate and consistent media delivery and exposure data, such as gross rating points and circulation
  
• Poor-quality sampling and market-research panels that undermine the use of many traditional tools for gaining consumer insight
  
• Opaque cost-accounting practices among marketers, their agencies, and media companies, including significant—but invisible—rebates
  
• High turnover at thinly staffed commercial organizations that hinders data tracking and analysis

Five Steps for Jump-Starting RDE Marketing Measurement:

• Build your team
• Work with what you’ve got
• Develop a “common currency”
• Map the road ahead
• Anchor the roots- anchor the roots of your marketing-effectiveness efforts firmly throughout your organization.

Original link to the post is here. 

Why Online Reviews Are Important?

I read this awesome post on HBR that prompted me to write this blog post here. Before I start discussing further, most part of this post is from that post.

With the growing availability of opinions from experts and users, the importance of a brand name had diminished. In the past, buyers typically made relative comparisons (“Is Brand A better than Brand B?”) or went by the maxim “You get what you pay for.” They were largely dependent on information provided by manufacturers in the form of marketing. Today, thanks primarily to user-generated reviews and people’s tendency to consult social media friends about purchases, buyers have other options. The wealth of peer-to-peer information and the unprecedented availability of expert opinions give them access to what’s known as absolute value—a rich, specific sense of what it’s like to own or use the goods they’re considering.

Every marketer is aware of the rise of online reviews and other sources of peer-to-peer information, but many neglect this trend and market products much as they did a decade ago. We believe that many companies need to dramatically shift their marketing strategies to account for the rising power exerted on future customers by the opinions of existing customers. The experts at HBR have created two tools to help managers do that: the influence mix and the O continuum.

The Influence Mix

Customers’ purchase decisions are typically affected by a combination of three things: Their prior preferences, beliefs, and experiences (which we refer to as P), information from marketers (M), and input from other people and from information services (O). This is the influence mix.

Think of it as a zero-sum game: The greater the reliance on one source, the lower the need for the others. If the impact of O on a purchase decision about a food processor goes up, the influence of M or P, or both, goes down.

In recent years O has taken on increasing weight in many categories, but plenty of exceptions remain. For example, habitual purchases (such as milk) tend to be dominated by P, while someone shopping for a toothbrush is most likely to be swayed by packaging, brand, pricing, and point-of-purchase messages—all components of M.

Companies need to ask: To what extent do consumers depend on O when making decisions about their products? We present the answers as points along the O continuum. The closer your product is to the O-dependent end, the greater the shift in how consumers gather and evaluate information about it.

Double Click The Picture For Better View

The O Continuum

Once firms understand where a product falls on the O continuum, they can consider the strategic implications in four realms:

Competitive position. In domains where customers depend mainly on O, branding takes on less importance, and newcomers find relatively low barriers to entry as a result. This is also apparent in the restaurant business: Research by Michael Luca, of Harvard Business School, suggests that in cities where large numbers of diners rely on Yelp reviews, independent restaurants tend to benefit, while chains and franchises often see their revenues decline. 

Companies in O-dependent markets can also diversify more easily than others, because new peer-to-peer information can overcome long-held conceptions about what a company is (and isn’t) good at. LG and Samsung have taken full advantage of this capacity, moving beyond their original core products (electronics) into a broad array of tech goods and home appliances.

In general, we see greater market-share volatility in domains where customers depend mainly on O. (Witness the swift declines of Nokia and BlackBerry.) Conversely, brand equity and loyalty can protect established players in O-independent domains; brands such as Clorox and Bud Light, influenced primarily by P and M, enjoy relative stability. O is also not of great concern to the likes of Grey Goose vodka and Hermès—brands for which prestige and emotional ties play an important role and quality is a given.

Communication. Let’s consider what happens in this arena for products suited to O-dependent purchase decisions. In recent years many camera buyers have turned to ratings and user reviews as their main source of information. This means that celebrity endorsements are less effective than they once were. Banner ads intended to create or reinforce brand awareness are not very successful either, because when it comes time to buy, the weight of trusted reviews usually overrides any residual effect of fleeting exposure to an ad. Instead, companies such as Nikon and Canon should focus on generating user interest in particular products and promoting an ongoing flow of authentic (and positive) content from O on internet retail sites.
Consumers are less likely to consult O about purchases that are not very important to them—most people don’t go on Facebook or Twitter to ask “What kind of paper towels should I buy?” or “What brand of detergent do you like best?” So marketers trying to reach O-independent consumers can be guided by some of the old rules, including many traditional M activities. P&G, for instance, can still benefit from persuasive advertising and eye-catching store displays for Bounty and Tide.
 

Market research. Companies in domains that are not susceptible to O can continue to draw on conventional market-research approaches, but those in O-dependent areas need to think differently. Market research usually aims to measure P—it tries to predict the kinds of products consumers will like by assessing their preferences in the past. But as purchase decisions become more reliant on O, rooting around in consumers’ psyches to understand P yields lower returns. For example, a market research study conducted in early 2007—before the release of the first iPhone—concluded that U.S. consumers would not be interested in a “convergent” device that combined the functionality of a cell phone, an MP3 player, and a camera. (Whoops.) What went wrong? The study had measured P, but as soon as the iPhone hit the market and early adopters began gushing over it, people became influenced by O. Instead of measuring individual consumers’ preferences, satisfaction, and loyalty, marketers should redirect resources to the systematic tracking, coding, and quantifying of information from review sites, user forums, and other social media. 

Product segmentation. A product’s location on the O continuum often varies across customer segments and from country to country. One group of consumers might rely primarily on O, while another might be more attuned to M. And some distribution channels are less conducive than others to O. (Shoppers in brick-and-mortar stores are often more susceptible to M than online shoppers are, for instance.) Companies should analyze different consumer segments and tailor their marketing strategies accordingly. When communicating with segments that rely on M, a company can use advertising to build top-of-mind awareness, persuade customers, and position its offerings—but those strategies probably won’t work for segments that rely on O. Marketers should also bear in mind that the degree to which a particular customer relies on O might vary with situational factors. For example, some of the people who take full advantage of O while shopping for electronics online may come under M’s influence on Black Friday, when ads touting deep one-day-only discounts abound. With not much time to decide or to consult reviews, they may pick up products impulsively, in the belief that “if it’s on sale on Black Friday, it must be a good deal.”

Biggest Challenge In Online Reviews

When we talk with companies about shifting their marketing mix in recognition of the rising power of O, we hear one consistent objection: Growing suspicion (and in some cases, proof) that online reviews are subject to manipulation and fraud. Some marketers believe that consumer reliance on O will decline as more shoppers become wary of deceptive reviews. We disagree. Yelp, TripAdvisor, and others are becoming increasingly sophisticated at weeding out fake reviews, and consumers are developing a better sense of which sites (and which individual reviewers) they can trust.

Consumers used to the richness of online reviews will ever return to relying on traditional M. Consider two data points. First, 30% of U.S. consumers say they begin their online purchase research by going to Amazon for product information and reviews; second, studies commissioned by Google have found that shoppers consult 10.4 sources of information, on average, before making a purchase. Voracious information-seeking has become deeply ingrained in many consumers, and we can envision no scenario in which they will see traditional marketing as a better provider of product information. 

The sources of O change rapidly. New review sites and game-changing technologies can suddenly appear. For instance, consumers who use smartphone apps such as ShopSavvy to compare prices can minimize the weight of M on their decisions even on Black Friday. The idea that a new website or app can undercut years of careful messaging may be deeply frustrating to marketers—but it is a reality they must face. As the influence mix evolves, success will come to companies that can closely track the sources of information their customers turn to and find the combination of marketing channels and tools best suited to the ways those consumers decide.

This awesome post can be found on this link.

Real Time Bidding (RTB) In Online Display Advertising

Today I stumbled over how the Real Time Bidding (RTB) in online display advertising world works, I must say it's quite fascinating stuff. The beauty of it is- "the response rate", it is soooo fast that you will be awestruck with this technology, anything between 300-500Millisecond !!

Check the steps I found from Wikipedia on how is the flow of Real Time Bidding (RTB)-

• A user's browser requests a webpage of a site that uses real time bidding
• The user's browser receives the HTML for the webpage. Embedded in this HTML is a URL tag for an ad request
• The user's browser makes a call out to the ad server
• The ad server calls out the SSP that this website is using. Sometimes SSP and the ad server are integrated such as 24/7 Real Media OpenAdstream or Google's DFP & AdX systems.
• SSP makes a call out to one or more ad exchanges
• An ad exchange makes multiple call outs (bid requests) to several DSPs trying to get the best price
• DSPs evaluate the bid request and decide how much they want to bid and respond with bids to the exchange
• The exchange selects the highest bid with a URL of the winning ad and returns that to the SSP
• SSP returns the winning bid to the ad server
• The ad server finally responds with an ad to the browser of the Internet user which started all these transactions

 The link to Wiki page is here.

I tried to capture the steps in the into graphical form so that it becomes more clearer with the explanation.

Real Time Bidding (RTB) Flow

Please double click the image for a better view.

Airbnb CoFounder Sharing His Story: Video

This is an amazing video from the co-founder of Airbnb which is a huge startup success story. In this video Nate talks about what was it really before they start getting the traction. If you are an entrepreneur, you will probably go through the similar stages what Nate mentions Airbnb went through in its initial phase, sure anyone would love to be Airbnb given its success. Check out the video now-

Virtual Customer Integration In New Product Development (NPD)

Involvement of customer into New Product Development is such a key, it not just allows you to engage customer from day 1 of new product development, but helps you in gaining customers when the product is launched into the market.

How & When The Customer Can Be Integrated Into The NPD

 (Please click the images for the better view)

Advantages of VCI in NPD

 When VCI has the Most Impact in NPD