Only 26% of marketers are able to measure their social engagement

According to a recent Social Media Examiner study about the social media usage of both B2B and B2C organisations, resulting in over 3000 respondents; the overarching majority of marketers (86%) claim an importance of social media to their business. Whilst this result comes as no surprise and seems to correlate with other surveys, it is interesting to note that a mere 26% of marketers claim a proficiency in measuring the social media engagement’s impact on their business. This numbers becomes even more staggering if the social media marketing experience is taking into consideration. 45% of responding marketers have been using social media tactics for 2 -5 years, 5% of this group even claims a social media experience of over 5 years.

With agencies pushing hard to have their clients engage in Social Media Campaigns (particularly in B2C), it is interesting that despite big data and ongoing digitalisation, the majority of organisations is still willing to invest money without being able to measure its ROI. To proof Henry Ford’s famous quote about misguided marketing spending wrong, it is inevitable to not only be brave enough to try new things (e.g. social media efforts are largely trial and error based) but to continuously work on defining bottom line relations to increase attributable marketing spendings to business results.

Some efforts to define the social media marketing ROI exist, such as MDG’s ROI of social media or the famous HBR blog about the calculation of a “like value” in Facebook but most efforts seem to lack consistency in measurement and a lack of bottom line integration. Engagement and conversation measures are being frequently reported and often lead to wild claims about social media campaign success with high reported engagement numbers, yet they too lack to correlate social media engagement to to bottom line results or business objectives. This is were the smart, engaged and eager marketer needs to start to employ digital metrics to track multivariate correlations and subsequently develop smart social media cause effect models.

 

 

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how much product choice is too much?

After having listened to Barry Schwartz TED talk (multiple times – if you haven’t CLICK HERE) as well as Dan Gilbert’s TED talk (if you haven’t – CLICK HERE) I couldn’t help it but observe how companies deal with the paradox of choice in a different manner.

From an economic perspective, increasing product choice, assumed costs can be controlled, should make a lot of sense. The economist trained mind thinks of course about a perfect world inhabited by an infinite number of homo oeconomicus, occupying an infinite number of price value points along the price curve, yet for one product class (perfect price discrimination). The marketer on the other hand, will join the discussion and argue that a finite number of heterogeneous target groups exist, displaying however homogeneous needs and wants (the basics of traditional segmentation). The mix of these two worlds is exemplified by Samsung; for the non-trained aspiring mobile phone customer, Samsung offers (at the time of writing) a staggering 145 different mobile phones. Note, this includes various carrier combinations. Switching over to TVs is even more confusing. One has to wonder, particularly after reading Schwarz’s books or listening to his talks, if brands are increasingly hurting themselves by increasing the number of product choices offered to consumers.

just a phone

According to Schwarz, increasing choice for humans lead to several negative effects but most of all a decrease in overall satisfaction which in itself sounds like a paradox, yet manifests itself in the following terms:

Opportunity cost of choice: the higher the number of options, the more attractive the 2nd, 3rd of nth option becomes to the consumer. In other words, with each option the value of opportunity costs increases until, in theory, it reaches a point of paralysed decision making.

Expectations increase: the more choice consumers’ perceive, the higher expectations become. The more unlikely however becomes, that set expectations will or can be met by the current product offering.

Doesn’t it also seem like a paradox to offer double digit product choices in one product category , assuming today’s stressed consumers have both the time and the drive to research product differences. Shouldn’t the smart marketer argue, that in the light of the ROPA effect (read here if you haven’t), diminishing cannibalisation of marketing efforts is hardly achieved with a complex and almost undistinguishable product portfolio? Is it still seen a sign of weakness in our society to reduce offering instead of enlarging the portfolio – after all, who wants to claim product offering declined under his or her reign?! Does it make sense to spread marketing budgets across +100 different product variances instead of focusing efforts to get one product message and positioning right? Wouldn’t it make much more sense to establish one dominant product design and then allow to establish alternative for price discrimination purposes instead of working the other way around: “let’s throw all we have and see what sticks the most – this will be our flagship product”?!

I argue that in the light of big data, marketers should increase their influence on the company’s product portfolio and not only emphasise on social listening post launch but also social rational pre launch.

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Applied gamification – a supermarket in Austria

I have blogged quite a bit about the topic of gamification and its application to drive user behavior. The use of leveling, scoreboards and ranks has been successfully applied, mostly with intrinsic motivators attached, such as status and public profile display. What I came across recently is however a great example of a gamification in a day to day application with amazing effects. An Austrian based supermarket “Billa” applies gamification scoring to induce an increase in spending.

The amazingness of this example is its easiness, customers spend 100 EUR and get a 10% discount, 200 EUR lead to 15% discount and 400 EUR to 20% discount. Tracking couldn’t be easier, to participate one is asked to use a store savings card and thus plays nicely into the see through customer concept, which makes any ROI calculation a relatively easy task.

Makes me wonder why this hasn’t been applied on a wider scale, particularly in this setting as it seems to heavily affect repurchase behavior and short term loyalty.

applied gamification - receipt

 

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If the sky isn’t the limit anymore… what is?

Redbull’s Stratos campaign has set a new dimension of campaign and social engagement with consumers around the world. It also sparked discussion about the terms paid, owned, earned and shared media, however seldom has somebody questioned if the reach for the stars and current campaign scopes are still in line with resource theories of the firm. I argue they are not, excess capital holdings allow certain organizations to device campaign stunts, driven by eager agencies to score the next big thing, without establishing a full campaign to business objective link.

Watch somebody jump from space vs. going to space yourself (Axe Apollo):

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Questions that should be raised by marketers and budget holders:

> Is the race for the most extreme campaign to gain a healthy and sustainable race?

> Is it just too easy to spend money on paid media to get audience attention through extreme campaigns vs. meaningful content stimulation throughout the customer journey?

> Are campaigns like Stratos and Axe Apollo really justifiable beyond the hype of press and bloggers? Shouldn’t we as marketers not look beyond total reach and claim target audience reach in meaningful numbers? What is it that we achieve with campaigns? Can we create meaningful links towards the bottom line? I argue big media allows us to do so but at the same time introduces campaign limits.

> As most marketing organisations are setup as cost-centres, don’t we have an obligation towards stakeholders and the firm to justify our spending even more so these days?

> Are we just making use of aggregated fluffy terms like earned or shared media to hide behind walls of agency influence and ego stipulation to have the biggest campaign? Does size really matter in that sense?

Paid, earned, owned and shared isn’t what is seems like – we need to dig deeper:

If we spend $20m on a campaign and estimate to reach x number of people on the premise of paid media, y number of people on the premise of owned and z number of people on the premise of earned and zz number of people on the premise of shared; do we really measure what is meaningful to the brand, to the bottom line and to our budget responsibility? Shouldn’t we segregate reach into current customer reach and potential customer reach, furthermore increase in sustainable purchase effects and short term campaign spikes? Furthermore, I argue that smart data allows us to construct a media model which assigns values to each theoretical nod, we can start to differentiate between dead-end reach, multiplication reach and bottom line effective reach.

Dead-end reach: non current and non-potential customers, low network degrees

Multiplication reach: non-current or non-potential customer with a value generation network degree, e.g. one or more nods are either customers or potential customers

Bottom line effect reach: the total of current and potential customers reached through the conglomeration of paid, owned and shared. This number should be in a healthy relation to both substitute media spendings (e.g. $ effort) and also the total number of people reached. If we assume our target reach is equal to a sample population, the sample to total population ratio becomes a statistical ratio and the marketer’s task is to find the sweet spot instead of trying to cover the entire population to also reach the target group by intersection effects.

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6 reasons why… forget it, this is just a funny ad from Adobe

Adobe claims a top spot in online advertising with their funny Super Bowl commercial (see below) and well, their “You can measure Social Media ROI ad”. In times of smart data (I still refrain from using the word big data to specify the use of data for decision making advantages), this should come as no surprise, yet as it seems, business schools (as I currently experience the no 1 ranked business school in Europe), marketers and organisations still avoid the ROI discussion and shift to the topic of online brand building. I particularly like how Adobe uses current stereotypical personas to play in their ads – which in my opinion should put 85% of today’s marketers (see their Super Bowl ad), advertising agencies and “consultants” to shame.

YOU CAN MEASURE SOCIAL MEDIA ROI…

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Adobe’s Super Bowl commercial… wondering who the “winner” is now:

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As always, if you made it this far, check out the Adobe blog for more – worth a visit.

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People spend 9 billion hours on Windows Solitaire… what about your employees?

Some fun theory to start with:

Below’s clip dates back to 2009 proving that with adding fun to dull daily tasks, people’s behaviour can be influenced by introducing play aspects. Whilst this study is inconclusive in nature due to timing and selection bias, the shown increase of people using stairs by 66% vs the escalator suggests still valuable points to take away.

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Critique on the “study” / stunt:

The introduction of the game element fun lead people to change short term behaviour on both an experimental and non-trivial level. The question however remains if the human condition to recognise patterns will lower the fun element in the long term and thus dis-validate the spike in stairs vs. escalator selection. In other words, when will it become boring to take the stairs vs. going back to the elevator? The discount of other external influences, such as presence of cameras, crowd effects and word of mouth add further to the question of validity of said experiment.

Stuff to think about:

Without going further into issues of this experiment, it should trigger thoughts on how a behavioural change can be prolonged (e.g. Skinner’s theorem on operant conditioning) and how, when and or if fun elements as game elements hit a ceiling. In above’s experiment, it is bluntly obvious as any element to prolong sustainable change and induce behavioural change is missing. Once you have walked the stairs 2,3,4 or 5 times, the fun part of doing so and the associated engagement level starts to decrease.

Current application of game elements on real world problems:

A lot can be learned far from the scientific side of behavioural psychology. The application of game elements to non-game environments to induce behavioural change effects has already found wide application in both business models and marketing techniques. On the business model side, Linkedin with its profile progression bar and contribution graphs in groups as premiered the application of game elements, namely progression and levelling. Newer applications include FitBit, Nike+ and many other behavioural change inducing products. Very creative application of game elements can be found in Jay Z’s decoded experience on bing which levered upon virality, social sharing and explorer type behaviour.

The list of applied gamification to market problems is almost endless, yet many industries, such as B2B in general lag fairly behind to acknowledge the advantages of utilising game elements in both internal and external setting. Whoever is better to cite than Kevin Werbach, Wharton School of Business, who taught one of the first courses ever on gamification.

Kevin Werbach on Gamification:

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Current issues in research:

I could probably go on about various game mechanics, their application to reduce intrusive messaging to players and and and but this serves little to no point for one very serious reason. Besides studies on game behaviour online and some Gartner studies predicting a fail of large junks of gamification applications due to design elements, the scientific foundation and relevant research to build a solid foundation on a larger scale is missing. I wonder why research hasn’t caught up with a growing industry and managers acknowledging the application of game elements to real world problems. Question to be answered and researched:

> When will we hit a gamification ceiling and how can this be overcome (e.g. the Zynga fall of FarmVille reveals cycles in game elements)?

> Marketers like advergaming and gamification for external applications, mainly to induce marketing messages on an less intrusive level to consumers. Yet when and how does message aversion develop to the increase in gamified elements in the real world. The same applies to advergames and in-game advertising?

> How can we apply design elements to create sustainable fun elements for prolonged engagement or is the concept of iteration to be internalised?

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Algorithmic location modelling to enhance customer behaviour profiling for marketers

Background: 

Location based services (LBS) or location based marketing (LBM) has seen an increase in adoption based on ongoing technology diffusion amongst consumers (e.g. GPS enabled smartphones  as well as service enablers such as Foursquare or Facebook places).

Gartner estimates about 800 Million active LBS users by the end of 2012, a figure to grow to 1.4 Billion by 2015, resulting in over $13.5 Billion LBS consumer induced spending. With overall mobile advertising to be expected to account for $20.6 Billion by 2015, consumer induced spending on LBS provides a strong indicator of future growth driven by navigation, social networks and location search. The increase of smartphone penetration in third world countries will most likely result in a 2nd growth phase for mobile marketing and with it, LBS.

Growth of LBS will be enabled by further mobile and and tablet adoption rates and thus placing location based targeting devices into the hand of consumers. LBS revenue is assumed to grow mainly on its main form of current revenue generation, advertising.

LBS development

While customer privacy remains an issue, current adoption rates of LBS suggests users starting to neglect privacy concerns and even access fully passive LBS services such as placeme. Current studies confirm this trend with 58% of consumers valuing benefits over privacy concerns.

Advantages of LBS / LBM for marketers:

> Enhanced listening features to gain access to consumer behavioural data
> Enhanced targeting features to create more relevant POS offerings
> Enhanced interaction features to elevate customer brand interaction with social, contextual and location relevant content
Emerging opportunities for higher level data mining:
> Behavioural mapping. This is something which should see strong developments. Similarly to the Google Page Rank, a location rank should gain access to algorithmic modelling of consumer journeys. E.g. with increasing data, patters are likely to emerge to attribute value to. A consumer coming from location a to location b might suddenly seem more valuable based on prior exhibited behaviour than a consumer from location c to location b.
Some examples:
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Who really won the Super Bowl ad frenzy

With millions spent on Super Bowl advertisements, agencies usually go crazy pre and post Super Bowl about who had the best creative, the funniest story, the most Youtube Clicks.

With the 4 million Dollar per ad on the big day, one could have done quite a bit online… see Digiday’s analysis.

1. Twitter Promoted Trending Topic (every day for a month): $4 million / $120,000 = 33 days

2. 8-day YouTube Ad Buy: $4 million / $500,000 = 8 days

3. 6+ Million impressions on Tumblr’s Radar: $4 million / $120,000 = 33 days

4. 50 million Forbes.com first-page interstitial ads: $4 million / $80 CPM = 50 million impressions 

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Direct Fan Engagement – what brands can learn from the music industry

The music industry and many artists are undergoing a vivid transformation from top down content producers and mass entertainers to connecting on individual levels with fans. Some artists, such as Chamillionaire capitalize on digital marketing and gamification effects for a higher level of brand engagement, which is impressively shown in the following clip (extract from the 2012 gamification summit). Worth watching & very entertaining.

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learnings from the clip:

> Authenticity counts

> Engage on personal levels

> Make the brand matter

> Budget isn’t the driver – creativity is

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3 steps to evolve your marketing from content to contextual

Over the last 2 years, the term content marketing has not only been coined but received wide acceptance within marketing circles. Content marketing became the new mantra to engage with customers on a wide array on both digital and traditional levels. Current studies show (link to a Marketing Prof’s article on B2C content marketing trends), that content marketing still receives great attention and for the most part, rightly so. As most studies confirm, over 85% of both B2C and B2B marketers keep or even increase their content marketing efforts in 2013 based on previous years budget spending.

The content marketing matrix, shines some light on the level of content marketing management possibilities but also highlights, that a very generic customer profiling is assumed.

content marketing matrix

Why is content marketing however becoming complacent with an overflow of content from all sides to a single consumer?

> Consumers follow less traditional funnel concepts but rely on multiple sources and a more diffuse buying decision making behaviour (see ZMOT by Google for some inspiration)

> Technology enables consumers to not just for ROPO (research offline / purchase online) but currently for RMPO (research mobile / purchase online) and RMPM (research mobile / purchase mobile)

> Influence of content to consumers decreases with the increasing emphasise placed on social sharing and social recommendation (e.g. great content marketing but 2 out 5 star rating)

How can a marketer deal with these changes in consumer purchasing behaviour and the increase of technology as enabler for new purchase decision making? 

1) Utilise digital data: with digital media in place, enabling big data to become smart data is easier than ever. It is however important to differentiate between wanting to know everything and being able to distill what is really important. Don’t get overwhelmed by the flow of data but control it!

2) Enable customer journey thinking: smart data allows you to follow single customers (don’t think stalking) but to determine their need at any given time. A housewife in Massachusetts using an Android based Smartphone might follow a different decision making journey than a college freshmen in San Francisco using a laptop in a coffee chain. Customers don’t want to be spammed with content but receive the right content at the right time. Banner blindness is not a sign of too much content but non-contextual content – just because I searched for a fridge doesn’t mean I want to see fridge banners for the coming two weeks.Don’t spam with content – be smart and enable customer’s to use it!

3) Less is more: Customer’s banner blindness, which served as an example for the increasing marketing message aversion, is just one example of content being misplaced, money and resources wasted. Follow the customer journey and anticipate in real time the needs and receptiveness of customers to your content. Use digital data to model the journey and most importantly track progress – add value to the customer journey but not noise. Use your budget wisely and at important decision making stages when the customer most heavily relies on external content to progress in his or her buying cycle.

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