Advertising That Works

Advertising That Works

Consumer electronics brands are turning back to traditional media channels as digital spend decreases in 2018.

Advertising impact can no longer be gauged one medium at a time. Earlier businesses could measure how its TV, print, radio, and online ads each functioned independently to drive sales. Now ads increasingly interact. For instance, a TV spot can prompt a Google search that leads to a click-through on a display ad that, ultimately, ends in a sale.

Insight is now sought on knowing precisely how all the moving parts of a campaign collectively drive sales and what happens when you adjust them. Until recently, the picture was fuzzy at best. Media-mix modeling, introduced in the early 1980s, helped marketers link scanner data with advertising and decide how to allocate marketing resources. For about 20 years, everyone gorged on this low-hanging fruit, until the advent of digital marketing in the late 1990s. With the ability to monitor every mouse click, measuring the cause-and-effect relationship between advertising and purchasing became somewhat easier. Marketers started tracking a consumer’s most recent action online – say, a click on a banner ad – and attributing a purchase behavior to it.

Combined with a handful of time-honored measurement techniques – consumer surveys, focus groups, media-mix models, and last-click attribution – such outmoded methods have lulled many marketers into complacency. They mistakenly think they have a handle on how their advertising actually affects behavior and drives revenue. But that approach is backward-looking: It largely treats advertising touch points – in-store and online display ads, TV, radio, direct mail, and so on – as if each works in isolation. Making matters worse, different teams, agencies, and media buyers operate in silos and use different methods of measurement as they compete for the same resources. This still-common practice, what a Harvard study calls swim-lane measurement, explains why marketers often misattribute specific outcomes to their marketing activities and why finance tends to doubt the value of marketing. As one CFO of a leading company said, “When I add up the ROIs from each of our silos, the company appears twice as big as it actually is.”

Seismic shifts in both technology and consumer behavior during the past decade have produced a granular, virtually infinite record of every action consumers take online. Add to that the oceans of data from DVRs and digital set-top boxes, retail checkout, credit card transactions, call center logs, and myriad other sources, and you find that marketers now have access to a previously unimaginable trove of information about what consumers see and do.

The opportunity is clear, but so is the challenge!

The Move to 2.0

In this new world, marketers who stick with traditional analytics 1.0 measurement approaches do so at their peril. Those methods, which look backward a few times a year to correlate sales with a few dozen variables, are dangerously outdated. Many of the world’s biggest multinationals are now deploying analytics 2.0, a set of capabilities that can chew through terabytes of data and hundreds of variables in real time. It allows these companies to create an ultra-high-definition picture of their marketing performance, run scenarios, and change ad strategies on the fly. Enabled by recent exponential leaps in computing power, cloud-based analytics, and cheap data storage, these predictive tools measure the interaction of advertising across media and sales channels, and they identify precisely how exogenous variables (including the broader economy, competitive offerings, and even the weather) affect ad performance. The resulting analyses, put simply, reveal what really works. With these data-driven insights, companies can often maintain their existing budgets yet achieve improvements of 10–30 percent (sometimes more) in marketing performance.

Powered by the integration of big data, cloud computing, and new analytical methods, analytics 2.0 provides fundamentally new insights into marketing’s effect on revenue. It involves three broad activities: attribution, the process of quantifying the contribution of each element of advertising; optimization, or war gaming by using predictive analytics tools to run scenarios for business planning; and allocation, the real-time redistribution of resources across marketing activities according to optimization scenarios. These activities may occur as sequential steps, or more likely simultaneously in practice; outputs from one activity feed into another iteratively so that the analytics capability continuously improves.

Attribution. To determine how advertising activities interact to drive purchases, companies need to start by gathering data. Companies are awash in data, albeit dispersed and, often, unintentionally hidden. Relevant data typically exist within sales, finance, customer service, distribution, and other functions outside marketing. Knowing what to focus on – the signal rather than the noise – is a critical part of the process. To accurately model their businesses, companies must collect data across five broad categories: market conditions, competitive activities, marketing actions, consumer response, and business outcomes.

Optimization. Once a marketer has quantified the relative contribution of each component of its marketing activities and the influence of important exogenous factors, war gaming is the next step. It involves using predictive-analytics tools to run scenarios for business planning. Maybe you want to know what will happen to your revenue if you cut outdoor display advertising for a certain product line by 10 percent in Lucknow – or if you shift 15 percent of your product-related TV ad spending to online search and display. Perhaps you need to identify the implications for your advertising if a competitor reduces prices in China or if fuel prices go up in Bangladesh.

Working with the vast quantities of data collected and analyzed through the attribution process, you can assign an elasticity to every business driver you have measured, from TV advertising to search ads to fuel prices and local temperatures. Knowing the elasticities of the business drivers helps predict how specific changes will influence particular outcomes. If the magazine ads’ elasticity in relation to sales is 0.03, for example, doubling the magazine ad budget will yield a 3 percent lift in sales, when all other variables remain constant. In short, analytics 2.0 modeling reveals how all driver elasticities interact to affect sales.

Allocation. Gone are the days of setting a marketing plan and letting it run its course – the so-called run-and-done approach. As technology, media companies, and media buyers continue to remove friction from the process, advertising has become easier to transact, place, measure, and expand or kill. Marketers can now readily adjust or allocate advertising in different markets on a monthly, weekly, or daily basis – and, online, even from one fraction of a second to the next. Allocation involves putting the results of your attribution and war-gaming efforts into the market, measuring outcomes, validating models, and making course corrections.

CE Brands Have a Duty to Dispel the Hype

From VR to drones to intelligent clothes, consumer electronics exist on the cutting edge almost by definition. For shoppers, the pace of innovation is thrilling. Every week a new, super-smart device hits the shelves, claiming to be capable of revolutionizing our lives.

What is more, it is only set to get better. With the Internet of Things (IoT) spurring on hyper-connectivity, whereby humans and machines will all be able to communicate as one, life admin could soon be a thing of the past. Forget wasting weekends in supermarket queues. Your washing machine will have pre-ordered your detergent to be delivered tout de suite via Amazon Prime. People will have time to do what they enjoy. Imagine that!

The challenge facing consumer electronics is not interest. Shoppers know that an enticing ecosystem of products and services thrives just a click away. Instead, it is their inability to differentiate, something that is only going to become more difficult as devices – and brands – become more interconnected. Because, consumer electronics are overwhelming to a typical shopper. How does he tell one device from another, never mind which is the right choice for him? To help navigate this alien landscape, shoppers need brands.

Pre-Internet, people would stroll into stores and, based on TV adverts or the brands they grew up with, demand certain things. Since then, as touchpoints proliferated, how people shop has totally changed. When buying a new TV, for instance, consumers spend an average of 7 weeks on the hunt, using 15 different touchpoints, from retailer websites to reviews to in-store sales staff. And still, the same dependency on brands rings true.

This does not seem to make any sense. Brands have more and more opportunity to educate and help shoppers make informed choices. But in the consumer electronics category, brands often enter a major pitfall. Shoppers are getting closer to, and more adept with, tech (thanks to freer information combined with easy access to smart devices) but they still need the nuances between different devices explained to them.

While shoppers know the perfect product is out there, they do not know how to identify it. This is because consumer electronics brands have yet to establish a common language to explain features to shoppers. The pace of innovation in the category is rapid, but people are not shopping for TVs, fridges, or mobile phones that often compared with other FMCG products. When they do, it is so confusing that they default to previous behaviors, which is not great if a brand has something really unique to sell that should distinguish it from competitors.

Asking if shoppers need assistance in-store just is not enough anymore – they started their journey weeks before that. Instead, brands need to get to know their existing and potential customers, identify the most important touchpoints on the path to purchase, and ensure their story is engaging and watertight across them. They need to relentlessly answer questions like: will it save me time and money? Will it make things easier? How will it enhance my life? Failure to do so leaves people with two choices: either they go for the brand perceived as best in category, or they stick with what they know.

What is more, instead of rising to the occasion, brands are often guilty of resting on their laurels. Remember Nokia and Blackberry? Once some brands have developed a reputation, they forget they are not the hero of their story – the shopper is. As such, too much time and money is spent pushing the brand. They have the tech, the tools, the know-how, and the engaged audiences. They dabble in VR and futuristic in-store activations, creating a veneer that, again, fails to help shoppers identify what is right for them. Consumer electronics brands need to craft a story that puts the shopper center stage.

There is no doubt the consumer electronics category is an exciting one, but it is in the habit of getting caught up in itself. In the not-so-distant future, all digital devices will talk to one another, cross-selling will be commonplace. Households will become digital microcosms, built around their human inhabitants. Bit by bit, they will become impenetrable to new brands. To earn their place at the table, brands need to work hard to understand what makes their shoppers tick and help them navigate this new world order.

Share this:

Leave a Reply

Stay Updated on TV Veopar Journal.
Receive our Daily Newsletter.