Archive for the ‘Mobile’ Category
October 19, 2009
“I’ve got Comes With Music for 12 months with my Nokia 5800… I’m not complaining about free music, but as soon as the 12 months is up I’ll go straight back to iTunes. Half of my songs download properly, then half of them don’t… .”, - scissormetimbers, Whirlpool Forum, June, 14th
From its release, Nokia’s Comes With Music (CWM) service has been an ambitious step by the handset manufacturer to develop unique customer services that diversify revenues as well as solidify customer loyalty to the brand.
In this sense, CWM has been designed as a ‘walled garden’; a virtual utopia of music choice, confined to particular handsets and particular software configurations.
But in the 12 months since CWM‘s UK launch, and its subsequent rollout across nine markets on four continents (including Australia), subscriber numbers have only reached 107,000 (23,000 in Australia since March 09).
A combination of telco resistance (because of their own music offerings), a poor user experience by some subscribers, as well as locking files to particular handsets, have all played their part in building resistance to the offering. (Did anyone miss the irony of a mobile player restricting the mobility of its music service?)
In recent Music Minds research, there was a wide level of scepticism to the idea of mobile phones becoming the primary portable music player. Device memory, battery power, interface design and menu navigation were all raised as practical concerns, let alone issues to do with data ownership, management and portability.
Even if the concept is generally applauded for its comprehensiveness, the music retail market is simply too competitive for any brand, even one like Nokia, to prosper without a seamless ‘plug and play’ platform.
In a market devoid of iTunes, CWM would have gone some way to differentiating certain Nokia handsets (vis a vis Samsung, LG and Motorola) and, more importantly, taken a reasonable slice of the music retail market. But iTunes has conditioned the market into accepting a certain pricing model, a certain way of selecting music and a certain technology experience. iTunes might not be the perfect model (for users or artists), but the market has determined it’s the best we have, and the perception of seeing every third person on a train or bus with white earplugs spinning their way through a music library, is a powerful endorsement of the technology.
In recent days Nokia has been hammered by a ‘told you so’ sentiment, primarily driven by advocates of DRM-free music and open platform technology. Now a new perception game starts to play out, this one more dangerous for Nokia. Where once CWM was seen as innovative, now the public’s perception will be more circumspect. Like the negative perception that smothered Microsoft’s Zune player, Nokia has to quickly change perception by changing the user experience.
May 4, 2009
Ok, so Victrix is a little late jumping onto the Twitter bandwagon, but given the hysteria surrounding Swine Flu - with little justification as to why the WHO went to DefCon 5 - maybe a little ‘late to market’ isn’t such a bad policy after all?
This is a case study of how Twitter Intelligence (TI) can sometimes having a profound impact on our (the brand’s) understanding of the consumer’s perspective as well as the questions and concerns which are typically raised in a word-of-mouth scenario.
And this is a major point: I’m not aware of anyone yet describing Twitter technology as a method to measure and monitor word-of-mouth, especially in metric terms such as ‘rate of diffusion’, ‘positive/negative’ sentiment, brand and competitor awareness.
In this example, we have comments, opinions and chats associated with one of Samsung’s most recent mobile phone releases, the Omnia touchscreen. Using PeerIn’s Sentiment Metrics platform we have tracked and quantified these references online - across typical websites, but more interestingly across social media and user-generated content. Included in this catch-all is Twitter communications.
This analysis captures references to “Samsung” and “Omnia” and identifies more than more 20,000 items across blogs (including micro-blogging), forums, websites and news services. In percentage terms, the split is 51%, 26%, 15% and 8% respectively. Micro-blogging, or Twitter, accounts for just over 1% of all comments, which is relatively high for a product-related ‘event’.
However, what it lacks in scale, the Twitter channel more than makes up for in sheer chutzpah. In others words, when you’re limited to 140 characters, your opinions, questions and answers are going to be couched in a very concise, direct and forthright manner. There’s simply no room or patience to waffle, procrastinate or pontificate. Though there’s plenty of opportunity to market, or dare I say it, spam.
In the context of understanding a mindset, the Samsung-related Twitters are pure gold.
“Phones I have my eye on Samsung Omnia and HTC Touch Pro2″
“got lots of games and most importantly a GPS for my Samsung Omnia that is free…holla!!”
“Does anyone want to swap a Samsung Omnia for an iphone?? It would make my day and I would actually think you are crazier than me”
“I returned the samsung omnia and got an htc touch pro…spent all day yesterday unlocking and flashing it…sweet as betch now”
“Goddamn Samsung Omnia. You’ve broken my heart and I’m thinking about leaving you for a Blackberry Curve. It’s not me, its you.”
“Nokia N97 comes with disappointing hardware. Samsung Omnia HD looks better and better every day.”
In these few examples, you have cases of competitor positioning (and awareness) as well as consumer insights into hardware and software configurations.
There are many other examples, but one thing Victrix has learnt very quickly about Twitter: don’t take everything on face value. While no doubt a flexible, responsive and convenient communications channel, Twitter is also increasingly susceptible to astro-turfing techniques, where product placements clumsily infiltrate innocuous Twitter comments. Case in point:
“What a beautiful sunset. I’m sitting by a blue lake and listening to Michael Buble from my Samsung Omnia.”
And you thought the close-up of the Ford badge in Casino Royale was gratuitous!
June 30, 2008
This is why mobile marketing is going to struggle to generate a return, much less goodwill amongst consumers…
This rubbish was served up in the form of a banner ad running on the Techcrunch blog. High marks for audience targeting but the promotion and execution was straight out of the Dodgy Bros. operating manual.
With the incentive of a $500 gift card, the promotion is simply designed to capture mobile phone numbers. It’s not certain if Woolworths itself is behind the promotion, but the brand is prominent enough to give the impression that the company’s marketing department has had some involvement in the sign-off.
Now the rub. Read the following text which appears on-screen after the individual submits their mobile number:
If you enter the received pin you will join the Wixawin subscription service. Stop service? Text ’stop’ to 19993500 | Subscription: 8 msg per month, $2.50/msg each way and $2.50 joining fee. Competition ends 31-12-’08 | Age: 14+ only - ask bill payer’s permission.
In short, for the privilege of entering the competition and submitting your personal details, you’re slugged with a $2.50 joining fee and $20 worth of spam each month! And if you respond to each of those messages, that’s another $20 in fees. Further, to ensure the gift voucher pays for itself 100 times over, the competition runs until the end of year.
That means if you fail to copy down the number to stop this abuse, you’re in for $120 worth of mobile spam when the year’s up, or $240 if you respond to each spam with an abusive text message of your own.
In many ways the mobile industry has no-one but itself to blame for its poor development as a legitimate and valued marketing service. Examples like this put real, constructive mobile CRM initiatives back another 12 months or more.
June 15, 2008
In the over-exposed setting of Cannes this week, Justin Milne, BigPond’s CEO, announced a mobile advertising strategy that is certain to have consumers cramming the exits looking for the nearest Optus reseller
His goal is to offer the Australian marketplace the most sophisticated, most complex system of ad targeting there is anywhere in the world and will use Telstra’s 3G network to deliver the capability.
His behavioural targeting utopia is to triangulate the individual’s location, mobile and online data, then overlay that with some trusty customer segmentation of its own, to arrive at some quantitative assumption (read: scoring) about a person’s purchase intentions.
Based on this theory, an individual with a Telstra 3G handset, who’s walking down Norton St in the Sydney suburb of Leichhardt, for example, would receive a Yellow Pages ad for a local restaurant, perhaps with a discount offer to sweeten the deal.
That ad could be based on any number of variables, including the fact that the person was in the general vicinity of the restaurant, or they had previously searched for “restaurants” on their mobile browser, or had browsed a website like CitySearch, or from a socio-demographic perspective matched an ‘urban sophisticate’ profile. Of course, the ad could also be triggered by any combination of these four elements.
The question will be how each ‘input’ is weighted to ensure the system has optimised to reach a person with a high enough propensity to buy a meal at the restaurant. Without the ‘smarts’ to do this, the likelihood of the person taking up the offer will be relatively low, and the restaurant will have waste significant advertising dollars on a very expensive targeting system (relatively speaking).
Milne’s ambition is admirable. His system is world-class (in a theoretical way), but there are some obvious holes in the data architecture sitting behind the system, not the least being how to capture online data to fit into the subscriber’s profile.
How does BigPond get its hands on data generated from non-Telstra related websites? If I’m a frequent news.com.au reader, with a penchant for restaurant reviews, how does BigPond know this, and if it doesn’t have access to this type of third-party data (online or off-deck in a mobile context), isn’t this already undermining the integrity of the ad targeting system, and therefore reducing its value to advertisers?
At best, BigPond is likely to have access to very limited subscriber data, as well as stats re: on-deck behaviour, perhaps data from third-party, off-deck sites (with permission), and perhaps (and it’s a big perhaps) data from Telstra-related sites (like White Pages, Citysearch, Whereis etc. And we’ll conveniently ignore the issue of cookie deletion). The only reliable data point in the whole system will be a geographic fix on the owner’s handset.
As for customer segmentation methods (like Roy Morgan, Mosaic or some other proprietary system), these are simply too broad and too generic to add much value by way of specific ad targeting.
This is the trick. A number of consumer research pieces indicate that individuals are partial to advertising delivered either online or via the mobile handset so long as it meets their criteria for relevancy, ie, it matches an actual need, either immediately or over the medium-term.
If BigPond gets this wrong, and the advertising becomes both frequent and inaccurate, then this so-called media player will be in a whole world of pain.
June 5, 2008
Driving along the freeway, near perfect conditions, and the speedometer reads 120km/h in a 100km/h zone. An oncoming car flashes his headlights and your immediate reaction is to reduce speed and continue cruising slightly under the 100km/h limit, knowing there are police ahead monitoring the traffic.
It’s a common scenario of how shared information between ‘consumers’ leads to a better outcome for some. Other drivers in the same vicinity, who don’t have that knowledge, wont be so lucky.
Some drivers who are particularly paranoid about being booked (and don’t want to slow down!) will most likely surf the available radio stations to get a traffic report in the vain hope there is news about a potential radar trap on their way home from work.
In this case, knowledge about a situation hinges on the economies of search, which in this case proves to be very inefficient.
Now bring in the ability for an individual or organisation to push information to a network of like-minded people, all of whom would benefit from having near-instantaneous knowledge about an event or situation at a time when they can most profit from that knowledge.
Further, even knowing your network of like-minded individuals are increasingly active at a certain time (an in a certain place) only escalates your own awareness that you are likely to profit, and are therefore more engaged in the network’s activity, ie, the information broadcasted by members. The visualisation of a consumer network through mobile location-based services (LBS) would do just that.
The ability of a customer entering a shopping mall, or even visiting the town’s commercial centre, to maximise the value from their shopping dollar is ultimately constrained in this regard by a deficit in knowledge - not knowing the pricing of all competing products or not knowing where all the sales events are located.
A mobile channel which pushes this information out to registered users not just once a day but potentially every time a retailer decides to offer a discount to shoppers in the immediate vicinity for the next hour (a micro-sale model, for example), is now challenging the three key issues which can optimise the value acheived by consumers and retailers in a physical retailing space - perfect knowledge about their surroundings, the efficiency of search and intra-day price adjustments to take advantage of the crowd’s spend-profile.
What Google did for search, mobile will do for retail. It’s as simple as that.
May 18, 2008
Last month alone, up to 59m Americans were exposed to at least one advertising message on their mobile phone according to research by Nielsen. Further, most of those recipients did not have a negative attitude towards this type of ‘intrusion’, despite the majority of messages delivered via Bluetooth.
There is a point in markets like the US and the UK now being reached at which there is a very strong need for a robust mobile analytics platform. Not only in terms of providing market aggregates, like growth rates and ad exposures, but increasingly by campaign and site performance as well.
However, the need to provide this data is arguably more urgent in the case of mobile, vis a vis the desktop Internet. The perceived higher risks associated with mobile, whether in terms of the user experience, the technical set-up or campaign performance, requires that there is a comparable level of measurement to validate the decision in the first place. For the most part, that measurement or post-campaign analysis is simply not forthcoming. Hence, the often false starts associated with mobile-mania.
The debate about mobile analytics is currently dominated by the likes of Nielsen and M:Metrics with their sample methodologies (essentially panels of mobile users), however, like desktop research, sample methodology is limited by its granularity, particularly around site activity.
In fact most desktop analytic methodologies have holes like Swiss cheese when it comes to their applicability to the mobile Internet. Further, when it comes to reporting performance across platforms, we’re asking for a whole world of trouble.
For example, Javascript which supports many desktop analytic applications like Google, isn’t supported very well by handsets - in fact less then 1% of handsets support Javascript. The code is also a significant burden to the page’s file size, affecting the user experience. Likewise, cookies are also an issue, either because the mobile browser doesn’t support them or won’t accept them.
A strong alternative now being developed and tested by several commercial groups is the use of specific user IDs for each visitor to a mobile site or link. The IDs are built into ‘redirects’ to the vendors servers, which then pass the user back to the intended destination. This would be applicable to search terms, 3rd party links, advertising links or if the user simply browsed the site.
The IDs then sync with links to the home pages, landing pages and then through the entire click stream through to downloads, forms etc. This is where the ‘rubber meets the road’ in the all important ROI analysis into mobile investments. Critically, the curret methodologies which dominate the mobile space cannot deliver this data with much integrity, hence the urgency to get this right in Australia when the tipping point in mobile activity, currently underway in Europe, reaches our shores.
March 30, 2008
Throw in a some decent useability around handset design and menu selection, add in an unlimited data plan, and you have the makings of a very serious effort to position mobile/wireless as the consumer’s preferred digital platform. Not an adjunct to existing screens, but a full blown, stand-alone interface with the person’s immediate surroundings, where ever they are.
As these usage stats prove, the iPhone’s first six months has revolutionalised data behaviour of handset owners; and not just be degree, but by magnitudes of 10 and 20 times ‘normal’ usage. For example, in the broader mobile market, only 1.4% of users view on-demand video/TV , compared with 7% for smartphone (RIM, Apple, Windows, Symbion operating systems) owners and 21% of iPhone owners.
There are some very telling indicators in this data. At the very least, as handset functionality improves, a seperate MP3 player will be almost redundant; which is more of issue for Apple than anyone else. Further, the symbiotic relationship between browsing and searching has some validity here, with an improved browser experience on the iPhone obviously having a marked impact on search activity.
In short, as the handheld browser experience improves (from standard to smartphone to iPhone), the consumer’s propensity to search rises exponentially. This has massive implications for business forecasts attached to mobile search, as market intell on the penetration of smartphone and iPhone technologies will have on content development issues.
Content providers, particularly news publishers, will be the category likely to experience the quickest up-tick in mobile audience numbers with the proliferation of smart handsets. In turn, there will be a similar upswing in video, blogging and social media activity, all of which now move in lock-step with the news cycle and overall product design.
For the lucky publisher which secures a spot on the user’s ‘favourites’ menu (and this is critical), there is likely to be a significant level of further drill-down on more content sections and more content types (video, audio, direct-downloads etc.) than what has been typically experienced from ‘wired’ users in the past.
In the Australian context at least, the market belongs to the first news publisher prepared to go beyond the simple m-site and push mobile technology to the next level of interaction, transaction and user experience. The outcome of which is likely to be the creation of another audience peak, this time between 6am and 9am - premising the mood and story leads for that other prime time of between 11am-2pm. Two peaks, two premium audience times, two different platforms.
March 30, 2008
Mobile Internet (predominantly 3G) now represents almost 35% of the entire Australian mobile population, with just over one in three (35%) Australians having accessed the Internet via a wireless connection at some point in the last 12 months. This growth is almost unmatched by any other digital technology (with the possible exceptions of the MP3 format and the iPod); and this is happening even before the proliferation of iPhone-like technology in Australia.
The optimism around mobile broadband (3G) as the preferred consumer digital channel is based on increasing evidence that the content preferences of 3G subscribers are more innovative, especially in the way many are prepared to apply their handset in a retail or point-of-sale environment to augment the experience.
In terms of profiling their broader content preferences, the differences between 2G and 3G users are profound, particularly in terms of the step-up in content/application usage.
While 84% of non-3G users, for example, have a preference for messaging and chat, that figure rose only slightly to 94% for 3G users. This slight difference between the two groups was consistent across most applications like ‘search’, email and address book/calendar functions where we already have an pplication saturation.
The larger differences, however, occurred in content areas like music (65% to 87%), weather (55% to 81%), games (47% to 65%) and movies (44% to 70%). In terms of the magnitude between the size of the two audiences, the shopping category experiences the third largest variation (+25 point difference), behind weather (+26 point difference) and movies (+26 point difference).
As the retail preferences show, when bandwidth and handset experiences improve, mobile will be less about microsites and ad-fed content, and more about transaction, location-based experiences. The augmentation of the retail environment using mobile devices and applications (eg bluetooth, phone scanning/photos, SMS codes) will come down to a burgeoning developer community, unencumbered by proprietory source codes and telco ‘walled gardens.’
The smarter retailers will encourage the development of these types of mobile applications, allowing their brands to be leveraged while the application does the ‘heavy lifting’ in terms of customer engagement. If the application is successful in delivering actual sales via the retailer’s mobile channel, then the more innovative agreements will allow the application owner to take a clip of every sale. This is the peak of performance marketing.
March 23, 2008
To paraphrase Rupert Murdoch, the industry simply doesn’t know its own future, its the wild west out there.
Despite this sentiment, its worth looking closer at US advertising revenue projections for the next four years, spread across 10 platforms. The accompanying data is averaged out across sources such as Veronis Suhler and TNS.
Ignore the absolute figures - they never project accurately - but pay attention to the relativities between platforms and the Compound Annual Growth Rates (CAGR). Both indicate that even within the context of digital, there is an emerging hierarchy, with specific reference to mobile, entertainment media (gaming), and pure play Internet.
Off a low-base in 2007, mobile and entertainment media indicate the highest CAGRs for any media category, followed by the pure plays. The bullish nature of mobile’s CAGR, for example, is justified by simple anecdotal evidence that the radical interface (and menu selection) design offered by Apple’s iPhone is already encouraging higher mobile data usage amongst its users (well above non-iPhone users). Once the likes of Nokia and Motorola join in battle, mobile data rates will sky rocket. This is a guarenteed market outcome in 2008. The only variable likely to short-change the result is a lack of local compelling content (again).
Of concern to incumbent media is the near flatlining of advertising revenue growth. The outlook for newspapers, broadcast television and directories drags down the sector’s CAGR to an anaemic 4.6%. Interestingly, outdoor scores a CAGR of 10.4%, aided by the proliferation of touchscreeen and LCD technology (think about the visual madness of Bladerunner).
Pure-play Internet will continue to grow market share through ‘bargain-basement’ advertising rates (relative to TVC and print), and the optimisation of audience data and targeting capabilities. In fact, if stronger efforts are made to accelerate the implementation of behavioural targeting in 2008/2009, then its reasonable to add a few points to the CAGR for pure plays over the 2007-2011 period.
February 13, 2008
Making up for arguably an ambivalent consumer attitude towards mobile Internet browsing, several industry players are taking some extraordinary game-changing moves to shake the telcos from their bloody-mindedness (and self-delusion) that they are, and will remain, the gatekeepers of the mobile Internet.
Google’s Android OS blasted onto the scene in early November 2007. What’s more, the Android announcement included the establishment of the Open Handset Alliance – a federation of some heavy hitters in the handset, software, hardware and telco industries.
Then another bombshell. Nokia announces at the Mobile World Conference the formation of the Nokia Media Network (NMN). Already the network will manage the mobile real estate of brands like AccuWeather, Discovery, Reuters, Sprint, and of course, Nokia’s own M-sites.
Two sweeping changes to the mobile space, both with the intention to consolidate a fragmented service-provider environment, where a lack of compatibility is doing little to encourage value creation in terms of content development, applications and media buying.
In less than a month, the international mobile industry now has a handset manufacturer playing the role of media and marketing broker for the mobile space, while a search specialist sets the agenda in terms of an open-source operating environment for mobile devices, then stumps up US$10m as a cash incentive for would-be application developers.
At a local level, Vodafone Australia takes the uncommon step for a telco of educating agencies and advertisers about the mobile Internet, specifically on how to incorporate mobile into a marketing plan and media schedule using Vodafone’s Mobile Advertising Portfolio.
Some great collateral has been circulated, clearly detailing key points around CPM rates, response rates, top-line demographic data, dimensions, how to buy and inventories. This is a tremendously beneficial step in the simplication of mobile Internet as an advertising platform.
However, there is one interesting “pre-requisite” for businesses deciding to build their own campaign microsite, rather than outsourcing it to Vodafone. That is, all external links must be removed and “no attempt to obtain the consumer’s mobile number can be made.” The point is there remain limits to a carrier’s ‘openness’, even while new market entrants emerge and traditional players change their spots.
This is an extremely dangerous period for any proprietory supplier or network in the mobile space. Telcos can view these developments positively, realising the enormous upside for their data revenues, or they can fight tooth-and-nail to maintain some semblance of a walled garden. The proliferation of virtual mobile networks is an added complication, suggesting an almost certain content war between operators to build and retain their on-deck audiences.
