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Why Mobile + Big Data = The Future of Events | It’s All Virtual

May 22, 2013 Leave a comment

Great Post from it’s virtual.

Why Mobile + Big Data = The Future of Events | It’s All Virtual.

 

Mobile + Big Data = Future of Events

Introduction

Lindsey Rosenthal (@eventsforgood) and Liz King (@lizkingevents) host a fabulous online radio show called Event Alley Show. On a recent episode,Lindsey and Liz interviewed Joe English about the future of events. Joe is Creative Director, Intel Developer Forums (at Intel). I was captivated by Joe’s take on the future of events:

The future is about contextual tools that bring information sources together about the audience.

When I ponder the future of events, I tend to jump directly to mobile apps, location awareness and other features tied to the smartphone. Upon further reflection, it occurred to me that mobility is a feature: part of a larger picture. And the larger picture is about the impact that events can make. In other words, what Joe said (above).

The mobile technologies of today will morph into new forms (of technology) tomorrow. So technology is the tool that facilitates context about the audience. And the better events can deliver “attendee intelligence” to sponsors, the more effective sponsorships will be.

Let’s take a closer look.

Step 1: Mobile-enable Event Attendees

The Double Dutch mobile event app

Image via Double Dutch.

Historically, events have been an inefficient medium, as far as data capture goes. Think about all of the “micro transactions” that occur within an event and how we’ve existed all these years without capturing them. Baby steps were made with post-event web surveys, RFID and badge scans, but the game changer has been mobile apps.

So step 1 in the future of events is already here. Event planners can choose from a wealth of mobile event apps. Michelle Bruno published anexcellent overview of the mobile app vendors at Event Tech Brief.

Mobile event apps provide a personal assistant to help event attendees find the right content, meet the right people and generally get the most out of their experience. Meanwhile, all of the activity enabled by the app creates a stream of data that can turn into actionable intelligence when aggregated and interpreted.

Step 2: Aggregate Data Sources into a Common Repository

Image via Grzegorz Łobiński on flickr.

There’s an opportunity for a new player to emerge in Step 2. And that’s a vendor-neutral “Switzerland,” who builds interfaces for the industry’s vendors to exchange data (from the vendor’s applications into Switzerland). Here are just some of the many data sources that exist at an event:

  1. Mobile event apps.
  2. Registration.
  3. Online/hybrid events platforms.
  4. Badge scanners.
  5. Twitter.
  6. Survey systems.
  7. Photo sharing services.
  8. Third party location apps (e.g. Foursquare).
  9. Other social network apps.

The role of Switzerland is to combine proprietary data (from vendor applications) with publicly available data (e.g. public check-ins, tweets and other social streams) into a common data repository. From here, the next step kicks in.

Step 3: Apply Big Data to Deliver Attendee Intelligence.

We now apply Big Data technology against this enormous pool of event-specific data. Let’s return to the vision of Joe English: “contextual tools that bring information sources together about the audience.” Let’s consider a few applications of this.

An eHarmony for Events

Photo source: User VideoVillain on flickr.

Amazon makes awesome product recommendations for you because it’s gotten to know you (via your mouse clicks) and it compares your “profile” to what similarly profiled people have purchased. Via our new data repository, we’ve now collected a wealth of event data.

So now we can apply some science (similar to what eHarmony does to pair couples) to pair attendees to attendees and sponsors to attendees. As an attendee, wouldn’t it be neat for Big Data to tell you, “here are the three sponsors you should go visit today.”

Intelligence to Make Sponsors Smarter

Imagine mining the Big Data repository to provide aggregated intelligence profiles to sponsors. Activity data could be sliced and diced across numerous dimensions, including topic and frequency.

For instance, at a healthcare event, the analysis identifies the particular healthcare sub-topics that are receiving the most interest. Throw in a little sentiment analysis on top of this (e.g. from profiling public data and event-specific chatter) and you have some interesting possibilities.

With this sort of data crunching, attendee intelligence could tell sponsors:

  1. The specific sub-topics to focus on.
  2. The probability that particular profiles of attendees will engage with you.
  3. Whether attendee sentiment positive, negative or neutral about your company.

While this technology won’t deliver more visitors to your booth, the intelligence gained can allow you to adjust tactics “on the fly,” resulting in a more organic uptick in attendee engagement with you.

Intelligence for The Event Planner

By aggregating activity and engagement data (from attendees) and marrying that with sentiment analysis, event planners can infer attendee satisfaction. The thinking goes: the more engaged and active you were, the more you enjoyed the event.

Throw in the sentiment analysis and you can validate this. So you’d now have this option: instead of surveying attendees about your event, you can use Big Data to give you the answer implicitly.

Conclusion

So that’s my take on how technology can be applied to generate the contextual tools needed for attendee intelligence. I’d like to thank Lindsey, Liz and Joe for inspiring this post!

Categories: Big Data Tags: ,

Social TV : du téléspectateur assis au téléspectateur engagé : Marketing professionnel – Le marketing pour les professionnels

May 19, 2013 Leave a comment

Social TV : du téléspectateur assis au téléspectateur engagé : Marketing professionnel – Le marketing pour les professionnels.

La social TV, on ne peut plus la zapper. Pas une émission de télévision sans des @ ou des # affichés à l’antenne. Après la TV connectée l’année dernière, c’est désormais la social TV qui est la star des colloques.

La social TV, on ne peut plus y couper. Pas une émission de télévision sans des @ ou des # affichés à l'antenne. Après la TV connectée l'année dernière, c'est désormais la social TV qui est la star des colloques...

La social TV, on ne peut plus y couper. Pas une émission de télévision sans des @ ou des # affichés à l’antenne. Après la TV connectée l’année dernière, c’est désormais la social TV qui est la star des colloques…

Des téléspectateurs qui parlent

Pendant qu’ils regardent la télévision, de plus en plus de gens ont sur leurs genoux un 2ème écran : ordinateur, tablette, smartphone… Autant d’écrans avec lesquels ils réagissent, interpellent ou commentent le programme en cours. Ils votent, consultent des photos, des articles ou des vidéos en lien avec l’émission en cours, mais surtout, ils tweetent. De plus en plus. Il s’est écoulé beaucoup de tweets sous les ponts depuis le mariage royal de Will & Kate en avril 2011 : 6.000 utilisateurs actifs, 13.000 tweets pendant la cérémonie. La cérémonie des NRJ Music Award en mai dernier a pratiquement multiplié par 150 ces chiffres, avec près de 1,8 millions de tweets… La spontanéité de ces pratiques, même si ce n’est encore qu’une goutte d’eau comparée aux audiences de télévision, laisse à penser que le potentiel est gigantesque.

Des chaines qui veulent en parler

Pour les chaines, la social TV apparait comme une aubaine, dans un contexte de transition un peu morose où tout le monde pariait sur la disparition de la bonne vieille grille des programmes. Avec la social TV, la consommation “linéaire” est revalorisée : le live devient encore plus live. Aussi, les diffuseurs rivalisent d’annonces et de tentatives sur le sujet depuis quelques mois. Les stratégies mises en œuvre restent encore très disparates, à l’image des multiples questionnements et pistes à explorer. Ainsi M6 ou TF1 avec son offre 2ième écran « Connect » développe une approche multiprogrammes plutôt standardisée. A l’inverse, chez France Télévisions ou Canal +, le point d’entrée est davantage la marque programme avec des interfaces uniques.

Ces nouveaux usages obligent implicitement producteurs et diffuseurs à ne plus faire sans leur public connecté. Le traditionnel modèle vertical de la télévision se fissure pour se rééquilibrer vers le public. Une nouvelle relation plus horizontale s’installe, où le public devient presque coproducteur du programme grâce à ses contributions et interactions.

Thibault Celier, directeur média chez Novedia Group et responsable de l'offre KindofTV

Thibault Celier, directeur média chez Novedia Group

Des annonceurs aux aguets

Pour les annonceurs, la social TV est la promesse ultime de dispositifs de communication qui allieraient l’efficacité du web avec la couverture de la télévision. Un téléspectateur sur son 2nd écran est une mine d’or. On sait d’abord ce qu’il regarde vraiment à la télévision et – au travers de ses différentes interactions – c’est autant de données acquises par l’annonceur ou le diffuseur pour alimenter des démarches CRM. La télévision ne fabrique plus du « téléspectateur assis » mais bien du « téléspectateur engagé », et celui-ci a beaucoup plus de valeur.

Avec le 2ième écran, ce sont deux logiques publicitaires très éloignées qui se rejoignent : celle de la télévision, avec la couverture massive et les « minutes de cerveau », et celle du web, avec les possibilités du ciblage, des impressions et des clics …

Dans une certaine mesure, c’est le malentendu fondateur de la télévision commerciale qui pourrait disparaître : la télévision ne vend pas ce que ses clients, les annonceurs, achètent. La télévision vend de l’espace alors que l’annonceur achète du GRP. La social TV, avec sa capacité potentielle de mesure exhaustive des actions publicitaires, permet d’aligner l’offreur et l’acheteur sur une même marchandise, avec les impacts potentiels sur la valeur du marché publicitaire. Derrière ce sont de nouvelles métriques à inventer – hybrides entre le GRP et le CPC – et des plans médias qui deviennent de plus en plus complexes à construire.

Des tweets au ROI

Le multitasking, lui, est aujourd’hui une réalité. Tous les chiffres d’usage convergent pour indiquer que plus des trois-quarts des gens consultent désormais un autre écran quand ils regardent la télévision. Au-delà des tweets, se profile derrière ces usages la baisse de qualité du contact TV pour les annonceurs.

Il devient de plus en plus urgent pour les annonceurs d’investir et d’exister sur ce 2ième écran pour recapter l’attention et soutenir leurs campagnes TV. C’est aussi l’opportunité d’aller plus loin en démultipliant par exemple des logiques de placement produit sans les contraintes réglementaires de la télévision. Le 2ième écran favorise l’achat impulsif : la durée entre l’intention et l’acte d’achat est réduite.

Enfin, pour une marque, le 2ième écran est un nouveau territoire d’expression : elle n’est plus « à côté » des programmes dans des tunnels publicitaires où il est difficile d’émerger, mais bien dans le programme lui-même. Pour les annonceurs, le 2ième écran offre de nouvelles possibilités de communication, plus proches des programmes et de l’événement, mais aussi des téléspectateurs.

Top 4 Digital Marketing Trends for 2013 | Visual.ly

May 16, 2013 Leave a comment

Top 4 Digital Marketing Trends for 2013 | Visual.ly.

Top 4 Digital Marketing Trends for 2013 | Visual.ly

“Top 4 Digital Marketing Trends for 2013”, our latest infographic, provides a comprehensive analysis of tools and technologies that will define the digital marketing landscape this year. It traces the impact of the digital revolution on consumer behavior and highlights key trends that marketers need to focus on in 2013. It provides insights on optimally utilizing various elements of a digital marketing strategy like mobile marketing, social media, content marketing and author rank, to offer greater reach, better relevancy and higher customer engagement.

Categories: Big Data Tags:

Twitter Acquires Big Data Visualization Startup Lucky Sort, Service To Shutter In Months Ahead | TechCrunch

May 14, 2013 Leave a comment

Twitter Acquires Big Data Visualization Startup Lucky Sort, Service To Shutter In Months Ahead | TechCrunch.

SARAH PEREZ

lucky-sort-logo-200x60

Lucky Sort, a Portland, Oregon-based startup behind a visualization and navigation engine called TopicWatch that helped to discover patterns in live data streams, has been acquired by Twitter. Terms of the deal were not immediately available, but the company has announced via its website that it will be shuttering its service in the coming months, and several members of the team will now be relocating to Twitter’s San Francisco offices to join the company’s “revenue engineering department.”

The startup had operated somewhat stealthily until early 2012, when word came out that it hasraised a half-million seed round from Neu Venture Capital, Invite Investments (founders of Invite Media) and several angel investors, including Adam Riggs (Shutterstock.com), BankSimple co-founder Alex Payne, plus chaos theory physicist, quantitative trading pioneer, and roulette wheel hacker Norman Packard, Ph.D., who became the Chief Science Officer at the firm.

Packard is not joining Twitter, but CEO Noah PepperJesse Smith, and Daniel Fennelly, are moving to San Francisco.

With the company’s first product, TopicWatch, users could sift through social media, government filings, news and commentary in real time to find, summarize and analyze any text-based content. It was more than a “social listening” or “sentiment analysis” firm – those were only subsets of its overall capabilities.

Analysis of Twitter data was also only part of what this platform could accomplish, as well.

luckysort-tacobell

In effect, Lucky Sort was a big data play – it used NLP (natural language processing) techniques to discover information from huge, unstructured data sets. What made it unique was its ability to derive structure without having to first define a database of nouns, verbs, etc. as traditionally would be the case with NLP. Instead, Lucky Sort was moved towards data mining through statistics rather than input ontologies.

Last November, the engine was put to practical use through a partnership with the social network for traders, StockTwits. The relationship offered the entire historical database of StockTwits (everything that had been tweeted or shared within the community), as well as a real-time feed coming into its service. These data sets were made available in Lucky Sort’s analysis interface, allowing investors to come in and examine how chatter in the StockTwits community has correlated with price action.

This could produce visualizations (like the one below), which could be operated via touch – including on the iPad.

Today, Lucky Sort says that three of its team members are headed to Twitter, and a plan to transition customers off of its platform is underway. Asked what he meant by Twitter’s “revenue engineering department,” Pepper would only say, “it’s where we’ll be shoveling coal into the money printing machine.”

However he did say that as far as he knew, Twitter is not interested in getting into the finance vertical itself. “They wanted our technology and expertise for other things,” he says.

Lucky Sort had raised a total of $600,000 before the acquisition, with $100,000 coming from Howard Lindzon, StockTwits CEO and co-founder.

The startup joins other recent Twitter acquisitions, including another previously data-focused servicecalled Ubalo, as well as others like We Are Hunted (which led to Twitter Music), Vine,CrashlyticsBluefin Labs, and more.

The company’s official announcement is below:

Lucky Sort acquired by Twitter!

Two years ago I started Lucky Sort with several friends. Our goal was to make huge document sets easier to analyze, summarize and visualize by building elegant and user friendly tools for text analysis.

Today I’m very excited to announce that our journey has entered a new phase: Lucky Sort has been acquired by Twitter!

Several of us will be moving to San Francisco to join Twitter’s revenue engineering department, so if you’re in the neighborhood and want to talk about text mining or data visualization give us a shout.

We’ll be helping current customers transition off our system in the coming months such that we can focus fully on our future at Twitter.

In building Lucky Sort we had an enormous amount of support from friends, employees, advisors and investors. It has been uplifting to have so many people help us and it highlighted just how much business is a social endeavour.

Best,

Noah Pepper
Chief Executive Officer
Lucky Sort

This story is developing….

Correction: An earlier version of this post said Packard was joining Twitter. He is not. 

Categories: Big Data, KPI, Twitter Tags: ,

The One Infographic About the Digital Revolution You Need to Understand | LinkedIn

May 13, 2013 Leave a comment

The One Infographic About the Digital Revolution You Need to Understand | LinkedIn.

One of the challenges of the digital revolution that we’re living through today is its complexity, and the broad range of implications that companies need to wrestle with. Consumers are shopping in different channels, often hopping across them to complete a single purpose – what are the teams you need to have in place to deliver what’s needed across that journey? Consumers are creating showers of data in their wake – how should companies make sense of it, and what skills do they need?

I love this infographic we created not too long ago because it attempts to paint a complete picture of the implications of this revolution. (You can find more on our Pinterest page).

As well as being choc full of useful data, it provides a big picture of what’s going on. This kind of broad perspective is more important than ever because the array of challenges and new technologies create huge temptations to focus on narrow issues without understanding how they fit into the broader business. What this infographic really highlights is that it’s so important to get many things right. Great data insights without a great product? Big waste. Great product that your customers don’t want? Big waste. Wonderful execution of a bad product? Big waste.

How are you getting the balance across data, design, and delivery right? Who’s doing this well?

Learn more about this topic and others on the McKinsey Chief Marketing & Sales Officer Forum site, and follow us on Twitter @McK_CMSOForum. And please follow me on Twitter@davidedelman.

 

8 Marketers Doing Big Data Right

8 Marketers Doing Big Data Right.

Bigdata

There’s no need for fluff and buzzword BS when there’s rock-hard data to draw upon. Look around the business world, and you’ll see marketers who are enhancing their products with data-informed decisions. When you consider the vastness of data sets like Google searches, commercial transactions, social networks, GPS and the connected fitness trend, it’s not hard to believe that as a society, we log about 2.5 quintillion bytes of data every day.

Research from 360i found that consumers spend almost $300,000 a minute shopping online; brands garner 350,000 Likes per minute on Facebook; and Twitter users send more than 600,000 tweets per hour. The magnitude and specificity of this information has given rise to the term Big Data. But unlike a lot of the buzzwords in our 30 Days of Buzzwords series, this term is here to stay, and we’re happy about it.

Below, we’ve rounded up eight CMOs and CEOs who are doing data right, and growing their companies thanks to data-driven insights.

1. eBay CMO Richelle Parham

Richelle Parham is responsible for conecting eBay customers with the thinkgs they love through integrated marketing campaigns. One of her biggest initiatives to date is eBay’s new data-driven homepage, “the Feed.” Consumers can “follow” categories of items — from Ray Ban Wayfarers to vintage typewriters to costume jewelry — and stay on top of the newest listings, whether they’re collectors or simply in search of something specific. Its “follow what you like” feature is reminiscent of Twitter, while the gridlike presentation distinctly Pinterest. In her role as CMO, Parham keeps an eye on analytics and searches for ways in which her marketing team can optimize its efforts. “I like when I have the opportunity to understand what inspires their path to purchase and what matters to them,” Parham has said.

2. Amazon VP Marketing Neil Lindsay

amazon

Neil Lindsay is Vice President, Marketing at Amazon, a company known for using data to create customer relationships and optimize customer service, whether it’s suggesting items or resolving issues. In recent years, Amazon began selling its data on customers to third-party companies as a marketing solution — unlike other companies, Amazon doesn’t offer browsing history; it knows what people want to purchase. Despite empowering other companies to market themselves better, Amazon has traditionally invested in its own product rather than in paid marketing opportunities such as TV ads — the company would rather grow by word of mouth, Lindsay explained at ad:tech in 2012.

3. GE CMO Beth Comstock

Beth Comstock is chief marketing officer at GE. The “big startup” has a whole hub of data visualizations to reveal information such as how much energy certain appliances use, and how much it will cost you. These visualizations bring attention to GE’s products while helping people make better choices. In a CES talk last year, Comstock explained that it’s her job as a marketer to find value in and make sense of the vast data sets available. “I get breathlessly excited about data,” she said.

4. Netflix CMO Kelly Bennett

Kelly Bennett is chief marketing officer at Netflix, and was previously at Warner Bros. He’s led the digital marketing initiatives for many major recent box office hits and strategizes the promotion of Netflix’s original content, including House of Cards. Netflix has gotten much praise for its algorithm that drives recommendations and continues to turn customer actions into a better experience, most recently with real-time processing. And it appears to be working — Netflix data usage comprises one-third of North America’s Internet data consumption.

5. Walmart CMO Stephen Quinn

The summer of 2011 marked a turning point for big-box retailer Walmart — it brought on a CTO as part of a massive effort to reinvent the company’s business model and birth a more flexible, entrepreneurial identity, namely in the area of ecommerce. To succeed in this endeavor, Walmart launched the social, mobile and retail-focused @WalmartLabs in Silicon Valley, and it’s acquired a handful of tech startups, including Kosmix and Vudu. @WalmartLabs developed the search engine, Polaris, which uses semantic search algorithms to understand what someone is searching for and thus, boost sales. On top of that, the lab’sSocial Genome Product culls through millions of tweets, Facebook messages, blog postings, YouTube videos and more to detect purchase intent and drive ecommerce.

6. Rent the Runway CEO Jenn Hyman

Data has always been an invaluable asset to Rent the Runway, as its analytics team uses it to make decisions on everything from marketing to operations and inventory buys. Early on, RTR’s data illustrated that 25% of its customers were adding an accessory to their designer dress orders, so RTR jumped on the trend. “Rent the Runway actually launched an entire upsell program on the site because of this strong data,” says Hyman. Strong data has proven to be essential in monitoring customer trends, and capitalizing on new opportunities for revenue growth. Our Runway, the startup’s search engine of UGC photos, was launched in part because women who had viewed photos of dresses on real women were 200% more likely to rent than those who have viewed a dress on a model.

7. Financial Times Marketing Director Caroline Halliwell

The Financial Times has a data team of more than 30 people, spread across three groups: Data Analytics & Campaigns, Data Product Development and Data Technology. Together, they are using data — namely audience data — to push the FT‘s circulation levels to new heights, and to make the paper’s advertising products more competitive.

The FT‘s data-gathering process begins with its paywall, which it set up in 2007. The FT.com asks users to register to read up to eight articles per month for free. Registrants — there are more than 5 million of them — are required to declare their email address, zip code, industry, job responsibility and position level. The FT uses that information to deliver more targeted advertising — advertisers could, for example, target a campaign to executives in the telecoms industry, or HR department heads in Brazil. The FT also maps patterns in readers’ behavior to help convert them to full-time subscribers.

8. Birchbox VP of Marketing Deena Bahri

A beauty subscription service obviously has to tailor to various complexions, hair types and looks, but Birchbox’s utilization of data goes far beyond these physical traits. “From the beginning, data has been an essential part of Birchbox’s growth and strategy … we use it to make important company decisions, and use it to guide us towards creating the best possible new products for our customers,” explains Deena Bahri, VP of Marketing of Birchbox. Birchbox utilizes big data when they launch a new service or offering, and for Birchbox Man they used both behavioral and survey data. By surveying subscribers, Birchbox discovered that there was a high demand for male-focused products; and after careful analysis of a Limited Edition Birchbox Man release in November 2011, the company decided to launch a dedicated subscription delivery service for men in April 2012. Ever since this success, Birchbox has continued to use survey and behavioral data to improve its offerings, deliver exactly what its consumers want and stay relevant.

 

Categories: Big Data Tags:

Why Digital Marketing should replace KPIs with EPIs

May 5, 2013 1 comment

Why Digital Marketing should replace KPIs with EPIs.

This is a guest post by Stephan Argent - a member of the Marketing FIRST Forum, the global consulting collective co-founded by TrinityP3

Marketers have long shared their Key Performance Indicators (KPIs) with their agencies as a measure that helps define direction and success in business or marketing efforts. But even today, we rarely see comprehensive digital metrics as part of the KPI list.

Why?

My guess is marketing teams are still struggling to define what to look at that would be really meaningful when it comes to “digital” KPIs.  And after closer scrutiny, initial entries – such as Facebook likes – get the chop before the first draft.  (And so they should – I think Facebook dislikes would be a more useful measure of what’s working and what’s not…)

The Digital World

So, what’s a marketer to do?  And what (digital) KPIs should marketers look at when evaluating agency performance?

Instead of KPIs, I’d like to propose “EPIs” or Engagement, Performance and Influence as metrics for digital success.

Engagement in my view should be the holy grail of digital effectiveness. I’m not as wound up as others on the concept of a “like” – I’d rather see longer time spent on my site or with my content.

Performance is ultimately what we should focus on.  Whatever your broader business goals are.

And influence is the reality of the new, socially connected planet which we share.

Unlike KPIs, each of these areas needs to work together and be looked at holistically in order to be truly effective.  Here are five examples of each as a reference point:

Engagement 

1.     Activity.  Consider the activity on your digital properties. Number of Emails / enquiries / new leads – even complaints.
2.     Web Traffic. Look at unique visitors / returning visitors / number of pages per visit
3.     Engagement.  How long are your customers engaged on your site – what’s their interaction with your social media properties?
4.     Analytics suite.  What does your analytics suite look like?  How effective is it at capturing a range of metrics that give you a holistic picture of your digital properties?
5.     Source of digital engagement.  Where are your enquiries coming from? Which properties – can you delineate between mobile and web?

Performance

1.     Sales / basket / order size attributed to your digital properties
2.     Year over year or month over month performance
3.     Cost per click / sale
4.     Number of inbound e mails / calls
5.     Response rates from online advertising / promotional activity

Influence

1.     Number of positive / negative conversations – how are they tracking over time?
2.     Search ranking, share of search – call it findability if you like
3.     How many sources of recommendations do you have for your business?
4.     How many negative sources are there out there?
5.     What / how many external links are there linking to your business?  Are they good or bad?

So while this is a general list and areas of Engagement, Performance and Influence will vary from business to business, the point is to hone the myriad of potential measures into an orderly snapshot of what makes sense for your business – from a digital perspective.

Whether briefing agencies, challenging agencies or indeed searching for new agencies, consider capturing and evaluating your own EPIs for better results – and better results from your agency.

 

Categories: Big Data, FutureofMedia, KPI Tags: ,

Infographic: Big Data Makes a Big Impact | English

Categories: Big Data

Real-Time Marketing is Driving the Long-Term Brand Narrative | Edelman Digital

Real-Time Marketing is Driving the Long-Term Brand Narrative | Edelman Digital.

First in a series of posts exploring real-time marketing and Edelman’s Creative Newsroom.

The real-time imperative is here. Consumers have higher expectations for responsiveness, participation and relevance than ever before. 42% of consumers think brands should respond to their questions within an hour. News, memes and trends are traveling faster than ever, as our attention spans get shorter, dropping by 58% in the last 10 years.

There’s too much information to process: there’s 60 times more content from brands in our newsfeeds than just two years ago. People have started ignoring everything on the periphery of their screens. They are 400 times more likely to survive a plane crash than click on a banner ad.

We’re focused on images – which have 5x more engagement on Facebook than non-visual posts – and what’s trending NOW.

These changes are fueling a real-time, creative content revolution. In order to break through the clutter, brands must create engaging, visual content that connects with consumers about things they are thinking and talking about in real-time.

Real Time Becomes Real

While interest in real-time marketing began to surge during the Oreo Daily Twist campaign in summer 2012, the Super Bowl was the true tipping point for real-time content, evolving from marketing debates about creative newsrooms to household conversations in the living rooms of millions of people.

After Oreo won the Super Bowl with its dunk in the dark post, dozens of brands jumped on the real-time marketing train. The first big test was the Academy Awards. Sensing a surge in interest, Edelman’s David Armano proposed – and brands used – the #OscarsRTM hashtag to track the branded real-time marketing efforts. Some posts were good. Many were not. All of the results were minimal.

Despite the mixed success of opportunistic content around the Academy Awards, the pace with which brands have adopted real-time content has only increased. The Harlem Shake surged from the antics of five Australian teenagers to dorm rooms, break rooms and boardrooms around the world in record time, reaching a billion views in 40 days, half the time it took Gangnam style to reach this milestone. From the Simpsons’ “Homer Shake” to Sony’s “Cloudy with a Chance of Meatballs 2”, many brands created their own iterations of the Harlem Shake. A few were wildly successful. But only a handful of the early videos created any kind of traction for a brand.

Brands jumped in on the declarations, including Pepsi Next which tried its hand at Hadoken.

The prominent placement of the Chic-Fil-A cup in the first Vadering photo led many to speculate that the company was behind the meme.

And even the Russian Army got in on Hogwarting.

The Promise of Real-Time Marketing

There’s good reason for brands to activate real-time marketing programs. Data from Edelman’s clients who are using our real-time marketing services has shown that this opportunistic content drives a 400% to 600% increase in engagement.

Like your favorite blog, most-informed friend or go-to news source, well-executed, real-time marketing can help a brand become the lens through which fans view conversation topics and trends that are important to them. Repeated engagement with real-time, relevant content builds anticipation for future stories.

This isn’t just about generating more likes on Facebook, views on YouTube, or additional retweets. It’s about the long-term health of the brand. Whether looking forward to the next product or the next story, customers who actively seek out a brand become its most loyal advocates long-term. Driving anticipation is the key to building genuine brand love.

In order to be truly beneficial for the brand, real-time marketing must align short-term, fleeting attention on the stories of the day with the long-term brand narrative. This real-time principle is similar to that followed by TV shows. Individual episodes tell a self-contained story that reaches a tidy conclusion at the end of the hour, but the episode must also advance the broader story arcs for the entire season. Viewers must be entertained today, but interested enough in what will happen long-term to tune in next time. If there’s a disconnect between these two objectives, people will tune out.

The same is true for brands, particularly in the context of real-time marketing. In order to keep fans interested and engaged, there should be a spectrum of posts that collectively address the audience’s varied interests, with each piece fitting into the same overarching storyline.

Choosing topics that are relevant for the brand, resonate with audience interests AND are timely will help ensure that real-time content has a long-term, additive benefit instead of just generating a flurry of likes that amount to fleeting interest.

Content creators should evaluate real-time opportunities based on three factors:

  • Relevant –Alignment with brand values, orientation and priorities online
  • Resonates – Mapping to audience affinities and fan interests beyond your brand
  • Timely - Stories that are driving interest and conversation online now

Real-time is About More than Being Timely

Content must be more than justvisual and timelyto succeed. It must also be prominent– appearing in the places where your fans are spending their time. It should be relevant to the audience – piquing their interest at the peak of conversation – when people are thinking and talking about a subject. Branded content also must be immediately recognizable at a glance in the feed, so that fans are more likely to read it, remember it, and credit the brand for the time spent with it.

This is where the effective blend of real-time and planned content is key.

There’s a difference between real-time marketing and relevant editorial content. True real-time marketing—in which an opportunity is identified and content is created in the same conversation cycle—should only represent a small, but important, fraction of your content mix. You can plan for most content through proper editorial strategy. We know that St. Patrick’s Day is on March 17th. We know two years in advance what days the Super Bowl and the Academy Awards are on. However, we don’t know when an unlikely pop star will break 1.5 billion views on YouTube, or when the lights will go out at a major sporting event.

Real-time marketing works best when brands are able to plan for what they can anticipate, and react quickly to what they cannot.

Putting the Theory into Practice

Edelman Digital manages 1,000 communities – and more than 100 million fans. We have been developing real-time branded content for our clients over the last 12 months. On average, these real-time creative posts generated 4 to 6 times the level of engagement of a typical post. After validating the approach and developing best practices along the way, we have formalized our approach to real-time marketing in the form of The Creative Newsroom.

We will explore Edelman’s Creative Newsroom model in a subsequent post. You can also find information about the offering in our white paper, The Creative Newsroom: Real-time Marketing is Driving the Long-Term Brand Narrative.

If you have additional questions, please ask them here in the comments or @montelutz.

 

2020: When online advertising meets mathematics – Cream Blog

April 26, 2013 Leave a comment

2020: When online advertising meets mathematics – Cream Blog.

A City or Wall Street worker of the 1980s who saw today’s financial markets would be, most likely, gobsmacked. For the most part, the ‘gut feels’ and instinct-based trading of yesteryear have been replaced by intricate computer-based financial modeling and statistical analysis.

Similarly, looking ahead to the likely transactions, executions, insights and analytics of advertising buys of the year 2020, we see an equally seismic shift. Currently brands and advertisers are just scratching at the surface of what data has to offer. In seven years’ time, data – and its mathematical analysis – will rule the roost.

By the year 2020, the skills of the ‘quant experts’ that financial markets have employed for many years will be used to transform the buying and selling of media. Sophisticated algorithms and forecast modeling will be widely used on both the demand and the supply sides, bringing down the cost of advertising and ensuring results will be quickly measurable. Gut feelings will give way to data provided in real time.

This type of forecasting, based on proven mathematical models, is the way of the future in digital media and is far superior to the ad-hoc sampling that is most prevalent in 2013. So what do brands and media agencies need to do now to prepare for this brave new world?

The answer, of course, is data. Data is to media what location is to real estate. Simply put, it is the key right now to building an advertising environment that uses the amazing capabilities of algorithms to forecast and measure the value of every transaction.

And so, media owners and advertisers should be taking steps right now to own all the data associated with their consumers. They need a safe, secure place to house that information, as well as the capabilities to derive insights and value from all facets and attributes associated with their business: audience profiles, device preferences and habits, environments, creative executions and performance. While at the same time, they need to educate consumers about the benefits of a more targeted, data-led approach and address their concerns – such as through initiatives like Your Online Choices.

In addition, we’re already seeing a significant level of fragmentation across multiple devices and this will only increase in the years ahead. As the industry grapples with the challenge of making money out of mobile and targeting consumers on multiple devices in meaningful and measureable ways, data and analytics become even more important.

The powerful combination of maths and data, algorithms and analysis, are critical to the three phases of advertising: pre-campaign forecasting and predicting; real time analysis of campaign effectiveness; and post campaign recommendations and insights. As the number and variety of attributes associated with all marketing campaigns continue to rise, and the measures of success on various devices diverge, the most advanced algorithms and analysis will be needed in order to define success.

By making mathematics and measurement – and data and analytics – central to their business today, publishers and advertisers will be set up for greater success in 2020. This means both also need to choose their partners wisely, as no company can hope to accomplish all this alone. Who, they should ask, can they trust to keep their data and their brand safe?

After all, many things will be different in 2020, but consumer trust in a brand will always be paramount. No amount of maths will change that.

This article was originally developed for the Wharton Future of Advertising Program’s Advertising 2020 Project 2012-2013, wfoa.wharton.upenn.edu/ad2020

By David J. Moore, chairman and chief executive, 24/7 Media

Categories: Big Data Tags: , , ,
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