London Foursquare Ad Agency Rankings (21.10.2010)
Showing posts with label Foursquare. Show all posts
Showing posts with label Foursquare. Show all posts
Monday, 25 October 2010
The Top London Ad Agencies by Foursquare Check-in (21.10.2010) [Infographic]
London Foursquare Ad Agency Rankings (21.10.2010)
Wednesday, 18 August 2010
Recommendation in the age of collaboration...
Recommendation has and always will be one of the most powerful drivers for product purchase. The power of friends & family singing your brand's praises will always resonate more than a basic advertiser's message. In the age of social media however, the way we communicate has fundamentally grown, and subsequently, so has the way we recommend products to others. The consumer of today has communication options that have expanded not only his social circle past geographic and cultural limitations, but allowed brands to create a conversation with the consumer that previously didn't exist. With all of this communication expansion, what has digital & social networking really meant for recommendation?
With so many social media choices, what does it mean for how people recommend?
The requirements for an effective recommendation are relatively basic. It requires an informative statement about something, given credence by the trust level of the reviewer and the perceived relevance of the information. As trust grows, so does the power of the recommendation. Alternatively, the more relevant the recommendation seems, either through timeliness or quality, the more powerful it becomes. So as consumers communicate over greater distances, faster speeds and with a higher number of casual acquaintances, what happens to the power of recommendation?
Product recommendations from our friends and family automatically gain power from existing trust and Facebook, as the social network du jour, is well positioned to exploit that. Through the 'like' feature we can easily share what products and brands we care for, slowly building a recommendation network amongst our contacts. The simultaneous distribution of friends' recommendations through news feeds, means that opinions about brands and products can be shared quickly and clearly, from both internal and external Facebook sources (thanks to open graph & FBML) and leading to content inside & outside of the network. However, though Facebook is well positioned to communicate peer recommendations, a high level of trust still relies on a close knit network. Recommendations from general acquaintances or those unknown outside of the network still lack the power given to closer 'friends'.
Outside of traditional social networking, recommendation needs to rely on other sources to build trust. While Facebook uses existing ties, social search engines & sites, such as Aardvark or Yahoo Answers, rely on the wisdom of crowds and perceived authority as trust arbiters. Aardvark , acquired by Google earlier this year, seeks to answer questions based on a hybrid model, pairing user answers through existing social networks and based on topics that an individual has claimed expertise. Sites such as Yahoo Answers or review sites such as Qype, utilize a voting or user hierarchy model to attempt to signal which individuals are the most trustworthy. By considering a user's grade and his recommendation relative to others, individuals can begin to judge the quality of information, without the trust found in traditional relationships.
Alternatively, incentive based networks such as Foursquare or Get Glue use a mix of existing ties and accomplishment markers to signal trustworthiness. Through gaining badges based on accomplishments, users are able to signal that actions or qualifications have been completed, meaning they may be more trustworthy sources of related information. Requiring action may be a more effective way than asking an individual to show expertise, but it also involves a clear signaling system and direct links between signals and knowledge. Conversely, recommendations through action (such as Foursquare check-ins or tips at a specific venue) also have the capacity to prove more trustworthy than other sources, given the increased effort required.
Regardless of network type, brands must make themselves available to users. Building trust through interaction and making content easily available to experience, recommend and widely share, can help brands to create and facilitate user to user communications. Be it creating a heavily produced piece of digital content for a large brand or simply curating the venue page or website for a small establishment, the ease of use with which a consumer can find, interact with or share content can aid with gaining effective recommendation.
The requirements for an effective recommendation are relatively basic. It requires an informative statement about something, given credence by the trust level of the reviewer and the perceived relevance of the information. As trust grows, so does the power of the recommendation. Alternatively, the more relevant the recommendation seems, either through timeliness or quality, the more powerful it becomes. So as consumers communicate over greater distances, faster speeds and with a higher number of casual acquaintances, what happens to the power of recommendation?
Product recommendations from our friends and family automatically gain power from existing trust and Facebook, as the social network du jour, is well positioned to exploit that. Through the 'like' feature we can easily share what products and brands we care for, slowly building a recommendation network amongst our contacts. The simultaneous distribution of friends' recommendations through news feeds, means that opinions about brands and products can be shared quickly and clearly, from both internal and external Facebook sources (thanks to open graph & FBML) and leading to content inside & outside of the network. However, though Facebook is well positioned to communicate peer recommendations, a high level of trust still relies on a close knit network. Recommendations from general acquaintances or those unknown outside of the network still lack the power given to closer 'friends'.
Aardvark's Social Search in Action...
Outside of traditional social networking, recommendation needs to rely on other sources to build trust. While Facebook uses existing ties, social search engines & sites, such as Aardvark or Yahoo Answers, rely on the wisdom of crowds and perceived authority as trust arbiters. Aardvark , acquired by Google earlier this year, seeks to answer questions based on a hybrid model, pairing user answers through existing social networks and based on topics that an individual has claimed expertise. Sites such as Yahoo Answers or review sites such as Qype, utilize a voting or user hierarchy model to attempt to signal which individuals are the most trustworthy. By considering a user's grade and his recommendation relative to others, individuals can begin to judge the quality of information, without the trust found in traditional relationships.
Badges & check-ins help to identify expertise
Alternatively, incentive based networks such as Foursquare or Get Glue use a mix of existing ties and accomplishment markers to signal trustworthiness. Through gaining badges based on accomplishments, users are able to signal that actions or qualifications have been completed, meaning they may be more trustworthy sources of related information. Requiring action may be a more effective way than asking an individual to show expertise, but it also involves a clear signaling system and direct links between signals and knowledge. Conversely, recommendations through action (such as Foursquare check-ins or tips at a specific venue) also have the capacity to prove more trustworthy than other sources, given the increased effort required.
So what do these differing online recommendation networks mean for advertisers and brands?
Regardless of network type, brands must make themselves available to users. Building trust through interaction and making content easily available to experience, recommend and widely share, can help brands to create and facilitate user to user communications. Be it creating a heavily produced piece of digital content for a large brand or simply curating the venue page or website for a small establishment, the ease of use with which a consumer can find, interact with or share content can aid with gaining effective recommendation.
Saturday, 17 July 2010
The Top 30 London Ad Agenices on Foursquare (for 16.07.2010)
Thanks to everyone who suggested new venues on Twitter, by email or in the comments last time. I've added quite a few new listings to the overall list. I'm hoping to upload the full list and simplified data in a few days, once I can plug it into some quick data visualization software for a post.
Also, I've fixed a bug in the aggregator that combined data from Proximity London & SapientNitro, so you should see these as distinct entries now.
As always, if you think that I've missed an agency or location to add to the search list, just email/DM or comment.
.jpg Version below (click to enlarge)
Friday, 2 July 2010
The Top London Ad Agenices on Foursquare (for 29.06.2010) [Infographic]
As always, if you think that I've missed an agency or location to add to the search list, just email/DM or comment.
.jpg Version below (click to enlarge)
Tuesday, 15 June 2010
London Advertising Agencies on Foursquare (14.06.2010) [Infographic]
As always, if you think that I've missed an agency or location to add to the search list, just email/DM or comment.
.jpg Version below (click to enlarge)
Sunday, 30 May 2010
London Advertising Agencies on Foursquare (28.05.2010) [Infographic]
Tuesday, 25 May 2010
How Powerful Are Virtual Incentives and Why are They Always Badges?
The introduction of Facebook's new badge for accomplishments system & website like 'Get Glue' (a recommendation engine using badges to encourage sharing) show that incentivizing on-line behavior through virtual badges is on the rise. While 'token economies' are nothing new and virtual incentives have been shaping behaviour for years (recent examples can be found in about any Facebook app), the manifestation of badges as a reward is quite interesting.
In a previous article about the psychology of Foursquare, we noted that Foursquare's badge system works to economize offline activity through online rewards. Check-in at a number of Starbucks and you get a 'Barista' badge, visit 20 pizza parlors and get the 'Piazzolo' badge. Working in concert with other operant rewards (items on Gowalla, titles on sites like Qype/Yelp, rewards/points in virtual games, etc.), these virtual items have some real behavioural change power. However, what are limits of operant behavioural conditioning through virtual badges and more importantly, WHY a badge?
To start considering the choice of badges as popular virtual rewards touches on the heart of what virtual items can be effective. Badges represent a perfect example of efficient signalers as rewards. Badges in the real world, just as in the virtual, are highly visible. They communicate an important quality or accomplishment to others in a succinct yet understandable way. Their public, yet simple nature gains its power by being understood across an audience respected by the wearer. Therefore, one can assume that the effectiveness of a reward badge is measured by how visible the item is to an audience, how communicative it is to the audience about the importance of the act and how much that audience is respected by the wearer.
Boy scout merit badges are a good example of this. Though I only attended one scouts meeting (an introductory session which caused me to decide that not wearing a uniform and camping sounded much more fun), I and others can understand the system of how members earn badges for accomplishments (such as fishing or first aid) from popular culture.This means that the badges, which are recognizable by a large portion of a population (from either respected group members or secondary cultural members) can easily convey prowess at an activity to a large group from their highly visible position on the member's uniform.
Virtual badges on sites such as Foursquare utilize this same mechanic. The badges stay on the user's profile page, where they are instantly visible to a respected audience (other users within the wearer's network) and simply convey the accomplishment of an act.
Through these criteria, the examples of the Facebook badge system & 'Get Glue's' seem to have serious challenges, but for different reasons. The Facebook badge system, which unlocks badges based on various network accomplishments (ranging from having 'x' number of friends to opening 'x' number of groups) will instantly get adoption, due to the large number of Facebook users. The audience, combined with the ability to place it directly on the profile page/news stream, makes the reward highly visible. In addition, the audience that the badges speak to have a minimum of respect with the wearer, as they happen to be the user's peers. However, despite these strengths, most of the listed accomplishments that the badges reward for are rather pedestrian.Where is the respect for getting a moderate number of friends or starting a few groups, when any user could do it relatively easily. In this sense, Facebook faces the challenge of getting users to care about the acts the badges represent, facilitating the items to communicate a respected act easily.
Alternatively, sites like 'Get Glue' face different challenges in implementing effective online badges. The site's badges (or 'stickers' as they are called) revolve around recommending various items to others, an act integral to building the attractiveness of the network. While Facebook's 'like' feature and open graph may quickly render the site's premise obsolete, the challenge amounts are large enough that other users on the network could respect the accomplishment. The badges are highly visible on the user's page, which leads to an ease of signaling about the accomplishment. However, the small size of the site's current audience relative to other related networks (Del.icio.us, Facebook. Mr. Wong, Stumbleupon), diminishes the power of the respected audience. A smaller possible audience to notice a badge requires a fervent/insular user base to maintain the same effect, placing great pressure on the site to attract repeat users and foster frequent activity.
In both examples, as well as other rewards online, the challenge generally falls within one of our three reward criteria. However, even through considering all three factors, user behaviour is highly unpredictable. Only through understanding the overall user experience for a website or network can we attempt to predict behaviour and only then can an effective reward economy be created.
In a previous article about the psychology of Foursquare, we noted that Foursquare's badge system works to economize offline activity through online rewards. Check-in at a number of Starbucks and you get a 'Barista' badge, visit 20 pizza parlors and get the 'Piazzolo' badge. Working in concert with other operant rewards (items on Gowalla, titles on sites like Qype/Yelp, rewards/points in virtual games, etc.), these virtual items have some real behavioural change power. However, what are limits of operant behavioural conditioning through virtual badges and more importantly, WHY a badge?
To start considering the choice of badges as popular virtual rewards touches on the heart of what virtual items can be effective. Badges represent a perfect example of efficient signalers as rewards. Badges in the real world, just as in the virtual, are highly visible. They communicate an important quality or accomplishment to others in a succinct yet understandable way. Their public, yet simple nature gains its power by being understood across an audience respected by the wearer. Therefore, one can assume that the effectiveness of a reward badge is measured by how visible the item is to an audience, how communicative it is to the audience about the importance of the act and how much that audience is respected by the wearer.
Boy scout merit badges are a good example of this. Though I only attended one scouts meeting (an introductory session which caused me to decide that not wearing a uniform and camping sounded much more fun), I and others can understand the system of how members earn badges for accomplishments (such as fishing or first aid) from popular culture.This means that the badges, which are recognizable by a large portion of a population (from either respected group members or secondary cultural members) can easily convey prowess at an activity to a large group from their highly visible position on the member's uniform.
Virtual badges on sites such as Foursquare utilize this same mechanic. The badges stay on the user's profile page, where they are instantly visible to a respected audience (other users within the wearer's network) and simply convey the accomplishment of an act.
Through these criteria, the examples of the Facebook badge system & 'Get Glue's' seem to have serious challenges, but for different reasons. The Facebook badge system, which unlocks badges based on various network accomplishments (ranging from having 'x' number of friends to opening 'x' number of groups) will instantly get adoption, due to the large number of Facebook users. The audience, combined with the ability to place it directly on the profile page/news stream, makes the reward highly visible. In addition, the audience that the badges speak to have a minimum of respect with the wearer, as they happen to be the user's peers. However, despite these strengths, most of the listed accomplishments that the badges reward for are rather pedestrian.Where is the respect for getting a moderate number of friends or starting a few groups, when any user could do it relatively easily. In this sense, Facebook faces the challenge of getting users to care about the acts the badges represent, facilitating the items to communicate a respected act easily.
In both examples, as well as other rewards online, the challenge generally falls within one of our three reward criteria. However, even through considering all three factors, user behaviour is highly unpredictable. Only through understanding the overall user experience for a website or network can we attempt to predict behaviour and only then can an effective reward economy be created.
Tuesday, 18 May 2010
Foursquare & Central London Transport [Infographic]
Lately, I and others have been looking at Foursquare/Gowalla & the like to analyze geolocation data and wrap our heads around what its all about (hence the explosion of Foursquare data in the blog lately). More robust data is being developed, but while this doesn't promise to do any of that, I thought it would be worthwhile to try my hand at another infographic. With this in mind, I thought that the network's potential in generating transport insight might be worthwhile and without providing anything groundbreaking, the takeaways from comparing how people register their travel were pretty interesting.
As mentioned in the graphic, people seem to be registering locations while on the go, as tube stations aren't nearly as popular as train & tube/train stations. I know that some locations are naturally busier, Charing Cross vs. Brixton for example), but the under performance of some tube stations in popular locations (Leicester Square), means that not nearly as many people are checking in after the fact as would be expected.
Aside from this, the variety of places people checked in is quite amazing. From buses (shown in the graphic) to planes & a few boats (not shown), people are dynamically logging information when possible.
Perhaps the most striking fact from the data however, was the lack of dual or superfluous locations. Being that most seek to be mayor of somewhere, you would assume to see more distinctions of tube vs. train stations (for instance, Charing Cross is only listed as one entity). The multitude of people who check in from platforms within a train station however (not shown in final version of graphic), may counteract some of this.
Overall, I think as the service grows, we should see more people fleshing out London's transport network in line with what we would expect. From this sampling of transportation options, the network is already beginning to be represented well.
[Development Notes: I selected a subset of tube stations to represent due to the fact that I was drawing the map underneath it. TFL is rather touchy about the rights to their map, so I wanted to make sure that mine was divergent enough to not be derivative (hence noticeable differences I've made sure are present).
If this goes over well, I'm considering expanding it to a longer version (including everything that I noted was missing), so if you have any thoughts or ideas, just let me know.
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.jpg Version (Click to Enlarge):
Wednesday, 5 May 2010
London's Agencies Squared: How London Advertising/Media Agencies Rank Up on Foursquare....
As I mentioned in my last post about the Psychology of Foursquare, I've been looking into data aggregation and analysis of geo-located networks lately. While I wouldn't want the blog to become a 'one concept pony', I thought it would be interesting to see how agencies around London use Foursquare, since adoption around the industry is key to driving new networks and ideas.
One aggregation engine & a list of IPA agencies later, I've managed to pull together a rough 'league table' of the top 25 advertising and media agencies in London by check-ins (as of 4/5/2010).
By taking the agency list and searching rather quickly through Foursquare, I've managed to compile the main Foursquare IDs for a variety of agencies (Currently 105 in total). I know many agencies have a variety of check-in locations within their offices (3rd floor desk with some interesting tips at a certain advertising agency...I'm looking at you), but I chose the most popular/obvious choice presented to me, much in the way a new visitor to an office might. I'm also aware, as many of you have probably thought, that there are many agencies left out by using only the IPA website list. If you have an agency you feel I've left off (there are many), and you have enough check-ins to place you in the top 25, message me on Twitter (@dubosecole), email me or leave a comment and I'll add your Foursquare ID on the list for next time.
One aggregation engine & a list of IPA agencies later, I've managed to pull together a rough 'league table' of the top 25 advertising and media agencies in London by check-ins (as of 4/5/2010).
| Agency | Id | Check-ins |
| 1. McCann Erickson Advertising Ltd | 172633 | 660 |
| 2. Wieden & Kennedy London | 219558 | 529 |
| 3. Agency Republic | 154743 | 460 |
| 4. Delaney Lund Knox Warren & Partners Ltd | 154868 | 446 |
| 5. MindShare | 161142 | 385 |
| 6. Dare | 154565 | 297 |
| 7. Saatchi & Saatchi | 244912 | 288 |
| 8. Profero Ltd | 161146 | 259 |
| 9. Digitas | 154598 | 227 |
| 10. PHD Media Ltd | 173059 | 217 |
| 11. Proximity London | 154900 | 187 |
| 12. Wunderman Ltd | 605057 | 178 |
| 13. Bartle Bogle Hegarty Ltd | 154630 | 178 |
| 14. Zed Media (Branch of ZenithOptimedia UK Limited) | 154651 | 178 |
| 15. MediaCom | 203677 | 178 |
| 16. Mediaedge:cia | 537324 | 153 |
| 17. Abbott Mead Vickers BBDO Ltd | 171053 | 148 |
| 18. LBi Limited | 154854 | 138 |
| 19. Publicis Ltd | 236312 | 138 |
| 20. MPG Media Contacts | 1200388 | 133 |
| 21. Media Contacts (Branch of MPG Media Contacts) | 1200388 | 133 |
| 22. Glue London Ltd | 523581 | 130 |
| 23. Ogilvy Advertising Ltd | 156590 | 128 |
| 24. Fallon London | 183035 | 122 |
| 25. MediaVest | 208064 | 116 |
By taking the agency list and searching rather quickly through Foursquare, I've managed to compile the main Foursquare IDs for a variety of agencies (Currently 105 in total). I know many agencies have a variety of check-in locations within their offices (3rd floor desk with some interesting tips at a certain advertising agency...I'm looking at you), but I chose the most popular/obvious choice presented to me, much in the way a new visitor to an office might. I'm also aware, as many of you have probably thought, that there are many agencies left out by using only the IPA website list. If you have an agency you feel I've left off (there are many), and you have enough check-ins to place you in the top 25, message me on Twitter (@dubosecole), email me or leave a comment and I'll add your Foursquare ID on the list for next time.
Friday, 16 April 2010
The Psychology of Foursquare
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Geo-location is quickly becoming the feature de jour for existing networks and startups. While lots of attention has been lavished upon existing networks adding locational features (i.e. Facebook, Twitter) and various location-centric networks (Gowalla, Rummble, Loopt, etc.), Foursquare seems to have taken the lionshare of public perception. For those that aren't familiar with the service yet, I'm not going to explain much about it here, however, various articles, the network itself and a good section of Mashable are more than willing to give you the basics. 
Considering Foursquare within the normal geo-location trend, its clear to see that it occupies a space that uniquely reaches the consumer. While each network can move from its place on the incredibly good looking Venn Diagram by adding features or emphasizing different functionality, in general, Foursquare occupies a space that aims to connect users while entertaining. This game/network hybrid, means that clear psychological principles can be used to explain how Foursquare works, why its going to succeed and what we can expect from it in the future.
How Foursquare Works....
At its heart, Foursquare is about facilitating users sharing their locations with their friends.Therefore, the value of the network comes from the amount of useful location information present for users. When we think about this as the network's main goal, it becomes clear how all the network's related features come together to encourage generative behaviour. Overall, 5 core Foursquare features exist outside of simply "checking in", these are:
- Mayorships
- Tips
- Tagging
- Badges
- Venue Specials
Mayorships are probably Foursquare's most obvious feature and the factor that firmly places the network within the 'gaming' spectrum of geo-location. Through assigning a mayor to a venue due to frequent check-ins, Foursquare 'operantly conditions' (encourages the intended behavior with reinforcement) for frequent interest and activity. The fact that most venues currently offer no formal response for being the mayor is a common sense rebuttal to the effectiveness of mayorships. However, if we consider the larger gaming environment, there are external benefits encouraging mayorship. The process of becoming a venue's mayor requires a minimum amount of check-ins at its least and a rather competitive streak at its maximum, therefore, achieving a mayorship and protecting it becomes a cycle of effort justification, ownership and competition. Concepts such as endowment effect, show that when consumers perceive something to be 'theirs', they place a larger value on it.While some people may become mayors of a venue due to frequently visiting it regardless of Foursquare, once someone owns the title, there becomes the presence of atleast a little bit of loss aversion to relinquishing it, as an increased value has been endowed to the title.
More tangibly than mayorships, badges enhance the competitive token economy that encourages check-ins. Whereas mayorships enhance the venue's attractiveness, badges enhance the check-in itself's attractiveness. Through providing variety to the base network activity, the user experience is kept novel and users have something to consider when considering whether to continue on with the network experience. The fact that badges are displayed on a user's page means that they are internally non-competitive while being externally objects to compare against ones own. The badges can also confer different information about a user's behaviour to others. The 'Swarm' badge (given when checking in with 50 people or more) requires collaboration or a knowledge of popular events, something that speaks to the user's openness. Other badges, such as the 'Superstar' (checking in at 50 venues) are easier to achieve as the user progressively uses the network, but still signal to others that the user is varied in his locations & interests. These signals may not seem to be worth much, but as a user's involvement within the network increases, so does his emphasis on the value of what he signals others.
Most tangibly, Venue Specials can help to reinforce the intangible benefits of mayorships and badges, by providing real perks to the token economy of checking in. Users who aren't fully engaged by competing for the mayorship of a venue on ownership alone can be swayed by deals such as: 20% of a meal for the mayor, free drinks for the mayor or 15% off purchase to those who check in. These real life incentives can help to condition checking in at non-promotional venues as well, as the behaviour becomes more routine. Within venue specials, those which offer a benefit to everyone who checks-in serve to encourage general behviour, while those that offer mayoral perks increase the value of owning a venue tangibly. Through both efforts, the value of interacting with the network increases, simultaneously increasing the value of intangible mayorship benefits or badges.
The cataloging of Venue specials within Foursquare allows the network to also provide value as a recommendation engine. As shown in the sweet sweet Venn Diagram above, Foursquare wouldn't traditionally play largely in the area of recommendations relative to services such as Qype radar or Rummble, but the ability to point out tangible deals close to the user, coupled with their Tagging & Tips functions, means that the capability to do such is there. Tips and Tagging deliver recommendation value to the user, while also encouraging contributors to display their knowledge of local venues. Where as the mayoral function encourages localized competition, tips & tagging encourage localized collaboration. These features may seem ancillary to the more emphasized features within the network, but they offer a valuable reinforcement factor for use through the provision of dynamic and localized information.
Why Foursquare Will Succeed....
I spoke to a post graduate business class last month on Social media usage and after discussing Twitter, covered the current geo-location trends. While only 1 person out of 39 had heard of and used Foursquare, the concept of geo-located data sharing was met with rather pronounced concerns and disdain. It was only after framing previous types of sharing to the class that many finally began to consider the concept. As I related to the students:
"If someone had told you in 2002 that you would upload holiday albums for other loose acquaintances or possible strangers to see, as well as allow them to upload and tag photos of you, some would balk rather loudly. If I had told you in 2005 you would be frequently posting small updates about relatively mundane aspects of your life, on a service for almost everyone to see, most would probably doubt it. Therefore, when I claim that in a few years most of you'll be sharing locations with your friends online, does it seem as far fetched as before?"This mental framing of what is acceptable and unacceptable to share online is highly subjective against what the general public is doing. As more people adopt geo-located services, through either Foursquare or during the roll out of such services on Facebook & Twitter, users will habituate and finally fully accept the concept.
What can we expect in the future from Foursquare?....
As we can see above, Foursquare's user experience and viability seem to predict a strong future for the network, but what can expect it to offer next? Looking at how the current Foursquare experience functions, atleast two logical areas for development exist: Expanding Venue Specials & External Platform Integration.
Foursquare check-ins at specific Venues in Las Vegas were broadcasted onto a digital billboard...
Outside of the network, Foursquare's future lies in developing External Platform Integration. The roll-out of geo-located features on Facebook & Twitter are only the start of the myriad of options a user has when thinking about using geo-location. Foursquare's future lies in being able to syndicate network information to other platforms and recieve information in return. The use of Facebook's own network to promote content should only be the start of Foursquare's platform integration. Connecting usage to other geo-located networks such as Rummble or Gowalla means that the reinforcing economy of Foursquare can spread further, while also minimizing a user's barriers to check-in. Users can't be expected to check-in regularly on multiple clients and until one network comes out as the king of geo-location options, the future lies in creating an ease of use.
Friday, 11 December 2009
Social Networks, Geolocation, Recommendations and Double Jeopardy....
Warren Buffet was attributed to once saying "Your premium brand had better be delivering something special, or it’s not going to get the business”, but is this necessarily true? While logic would dictate that those brands which charge more must deliver a greater value in return, theories such as Ehrenberg's "Double Jeopardy" highlight the power larger brands have in the market place."Double Jeopardy" as described by William Mcphee and more famously, Andrew Ehrenberg, describes the concept that lower market share brands face a double challenge in competing with larger brands as they lack market share and brand loyalty from consumers. In such situations, the advantage large brands have from such jeopardy may encourage consumers to repeat purchasing behavior on factors beyond the value delivered by a specific purchase.To combat the advantage large market share brands have in the market place, smaller brands much differentiate. However, as large brands hold the advantage of possessing the promise of a standardized consumer experience, smaller brands must assure the consumer of quality, while still differentiating in tangible ways from larger competitors. Certain sectors allow for this more so than others, with clothing and food retailers serving as an example where double jeopardy and large brand advantage is chipped away by factors such as convenience, location, product differentiation and varied cost. In an example of such, Pizza Hut may provide a standardized dining experience over the Italian bistro down the corner, but consumer taste may eschew what is seen as pedestrian fare for a more personalized experience.
Using the food retailing example further, it becomes clear how smaller market share (i.e. non-chain) restaurants face the dual challenge of differentiating in image while still assuring the consumer of quality vs. larger chain restaurants. Segments of consumers may always ignore larger brands out of principle (I for one irrationally loathe Arby's), but attracting the majority of consumers hinges on convincing them of not only an interesting and different product, but also of a level of performance and quality. The development of social media use within the last decade provides a unique opportunity for such retailers. Large brands have the challenge of convincing users to trust them in a way small brands don't. The "corporate stigma" of such means that smaller brands have the opportunity to gain consumer trust quicker. While these brands still have to convince consumers of their standard of quality, they have the ability to confer an earnestness to their image that goes well with the communication model found in social media.
The ability of recommendation sites to get the word out about smaller retailers works both ways....
With the benefits of sites like Qype, the next issues for smaller brands and reputation in social media becomes the level to which user recommendations are trusted by others. A recommendation from a trusted source or with demonstrable elements can hold more impact than a glut of others. With the advent of microblogging sites, reviews have become much more instant, allowing users to confer a level of immediacy to their thoughts on smaller brands and retailers. While sites like Twitter may trim the amount of detail that can be given about a business or consumer experience, it does allow for opinions to be disseminated while still in the retail experience. Furthering this, geolocated services such as Gowalla, Foursquare, Rummble, Loopt, Dopplr, etc. add perhaps the highest level of authenticity to consumer reviews, confirmation that the reviewer is currently there or was in the past. By demonstrating consumer action, these services extend the depth of consumer reviews, as well as opening new avenues for promotion through their network.
Just a few of the many networks that are driving the ability of small brands to establish big loyalty
The opportunities afforded by social media channels may challenge the traditional idea of brand loyalty and scale, but they can be co opted in both offensive (small to medium brands) and defensive (large brands) ways. For small to medium companies attempting to use social media advocacy to build their brand, its important to remember a few concepts:
1.) Make sure the product delivers on its claims....no amount of advocacy will help (or actually be present) if the consumer experience is negative
2.) Be honest about how your product fits into the consumer's mind.....performance and reputation building will function differently for different products. People are more apt to recommend certain product types overothers.
3.) If the product fit is right, take advantage of the enthusiasm of networks and network users to grow their community....Just monitoring what people are saying is fine, but to actually chip away at large market share brand dominance, offensive measures promoting consumer involvement are useful. Programs such as Foursquare's "Foursquare for Businesses" initiative are useful to go beyond user recommendations to user interaction.
Larger companies face a more defensive structure when dealing with social networks and their brand loyalty. Without the organizational agility of smaller to medium sized brands, loyalty has to be protected through more thoughtful measures:
1.) Make sure the product and the surrounding associated products....no amount of advocacy will help (or actually be present) if the consumer experience is negative or if brand perception is firmly entrenched. Larger brands with multiple locations are at more of a disadvantage when it comes to standardizing the consumer experience.
2.) Use the scale of the brand to respond robustly to consumer comments. Unlike smaller brands, large brands aren't as likely to be able to build up earnest consumer recommendations as quickly without overcoming perceptions about corporations and size. The increased resources of big brands means that one can go beyond reacting to consumer reviews and opinions and actually respond, rectify and encourage advocacy.
3.) Don't simply match what smaller brands are doing to increase advocacy, surpass it. If the resources are present to dwarf smaller brands interaction with the consumer, do it. Consider social network partnerships (as long as it fits the brand identity) or cross network promotions. The more users that can be gathered through the brand's scale effectively, the better.
While the points made about double jeopardy and social media don't easily extend to all market categories, the original concept stays the same. Consumers may be more apt to review bars, pubs, restaurants and other retailers more than cereal brands, but that doesn't mean that something like smaller FMCG breakfast products can't leverage some consumer sentiment to affect distribution and retailer adoption. Within the above example, double jeopardy and brand loyalty is affected by inherent factors within the restaurant market, however the idea is clear that the way brands maintain and generate loyalty and adoption is changing rapidly due to the ongoing advancements in social media.
Thursday, 17 September 2009
Tweet it your way? Twitter's Capacity for Consumer Sentiment Measurement - Part I
I know two Twitter posts in a row (4 if you count parts coming tomorrow and over the weekend) may seem a little excessive, but with all the news surrounding the service right now, I'm writing my ongoing fixation off to the influence of news coverage and marketing zeitgeist. With today's valuation of Twitter at the $1 billion mark (paltry compared to the estimated $8 billion value of Facebook, but impressive none the less), attempting to quantify the various uses for the service seems rather envogue.
From a marketing perspective, Twitter's capacity to deliver a breadth of consumer thoughts is already well understood. Typing a company's name into search.twitter.com or the homepage link is a rudementary proof of the torrent of thoughts available about a product or business. While some product sectors produce more insight than others (luxury/aspirational products, global brands, recreational products and the like lend themselves to more conversation than the more mundane or basic such as household FMCGs and financial services), the ability to look into the amorphous "crowd" and pull out buzz is invaluable. This utility has spawned not only business interest in the website itself, but has also impacted 3rd party services. Twitter specific services such as Hootsuite harness the reasonably accessible Search and REST APIs within the network (ease of use being something I can attest to having written my own Twitter analytics software),in addition wider buzz tracking offerings have added functionality beyond blogs and forums to include Tweet aggreagation.
Anyone who's familiar with the advanced search functionality of Twitter knows that added value stems from the ability to segment messages gathered from the service. Searching by user, user mentions, network position from a fixed point (if you're willing to code a large amount of secondary aggregation data) and geographic location mean that user's messages can gain a relevance. However, with this wealth of possible data, what actionable insights can be generated?
At the most basic level, number of mentions and time series data on mentions are the easiest data to procure. By simply collecting a period of data on a term, one can compare activities such as news coverage with Twitter activity.Combining message amounts with other competitors in a sector can generate topline statistics on its performance and loosely gauge twitter activity possibilities for sector ("market tweet size" if you will) and company share ("share of tweet" if you won't).
At a slightly more advanced level, user mentions and user profiling are possible, as well as multiple searches to determine activity by various geographic areas. Combining this with analyzing Twitter profiles, a brand can gain insights on what type of users are talking about the brand (though the value of such topical profiling is limited). Geographic searching allows not only for regional activity comparison (great for larger brands), but also for specializing a search area (great for smaller brands and singular locations such as a local chain of restaurants).
Finally, data such as message content, message platform and links can generate insight on user behavior when mentioning the brand or associated content (through seperate link spidering - something that is easier said than done with bit.ly and tinyurl's api limits). Perhaps most evidently, the time consuming process of actually reading every user message can generate a specific picture of trends emerging around a brand. Depending on the volume of messages, this can be unfeasible, confusing or flatly impossible; in situations such as this, I've found that porting messages into a word cloud generator such as Wordle can provide top line figures on atleast the most basic of consumer sentiment.
For the future, I see the nature of "real-time" search analysis becoming even more reliable and specific. Services such as Foursquare (Hurry up and get to London!) are ushering in consistent geolocation of messages in a system that encourages more detail than simple experiential tweets (i.e. "I'm off to get lunch at Business X" vs. "I just had horrible service at Business X"). Furthermore advances in automated semantic analysis are making the process of analyzing user messages for trends and sentiment quicker and more accurate, something that will be highly appreciated by those attempting to read the breadth of aggreagated content.
In considering consumer sentiment measurement, perhaps the best way to illustrate current and future possibilities is to provide an example. Tomorrow in Part II, we'll take a real-world example and generate some topline data on Burger King within the UK utilizing a variety of web tools.
From a marketing perspective, Twitter's capacity to deliver a breadth of consumer thoughts is already well understood. Typing a company's name into search.twitter.com or the homepage link is a rudementary proof of the torrent of thoughts available about a product or business. While some product sectors produce more insight than others (luxury/aspirational products, global brands, recreational products and the like lend themselves to more conversation than the more mundane or basic such as household FMCGs and financial services), the ability to look into the amorphous "crowd" and pull out buzz is invaluable. This utility has spawned not only business interest in the website itself, but has also impacted 3rd party services. Twitter specific services such as Hootsuite harness the reasonably accessible Search and REST APIs within the network (ease of use being something I can attest to having written my own Twitter analytics software),in addition wider buzz tracking offerings have added functionality beyond blogs and forums to include Tweet aggreagation.
But what do customers really think about the Baconator(TM) Hal?
Anyone who's familiar with the advanced search functionality of Twitter knows that added value stems from the ability to segment messages gathered from the service. Searching by user, user mentions, network position from a fixed point (if you're willing to code a large amount of secondary aggregation data) and geographic location mean that user's messages can gain a relevance. However, with this wealth of possible data, what actionable insights can be generated?
At the most basic level, number of mentions and time series data on mentions are the easiest data to procure. By simply collecting a period of data on a term, one can compare activities such as news coverage with Twitter activity.Combining message amounts with other competitors in a sector can generate topline statistics on its performance and loosely gauge twitter activity possibilities for sector ("market tweet size" if you will) and company share ("share of tweet" if you won't).
At a slightly more advanced level, user mentions and user profiling are possible, as well as multiple searches to determine activity by various geographic areas. Combining this with analyzing Twitter profiles, a brand can gain insights on what type of users are talking about the brand (though the value of such topical profiling is limited). Geographic searching allows not only for regional activity comparison (great for larger brands), but also for specializing a search area (great for smaller brands and singular locations such as a local chain of restaurants).
Looking at the UK BK Tweets for the last few months makes me want to have a "Chicken Fries Whopper" for some reason
For the future, I see the nature of "real-time" search analysis becoming even more reliable and specific. Services such as Foursquare (Hurry up and get to London!) are ushering in consistent geolocation of messages in a system that encourages more detail than simple experiential tweets (i.e. "I'm off to get lunch at Business X" vs. "I just had horrible service at Business X"). Furthermore advances in automated semantic analysis are making the process of analyzing user messages for trends and sentiment quicker and more accurate, something that will be highly appreciated by those attempting to read the breadth of aggreagated content.
In considering consumer sentiment measurement, perhaps the best way to illustrate current and future possibilities is to provide an example. Tomorrow in Part II, we'll take a real-world example and generate some topline data on Burger King within the UK utilizing a variety of web tools.
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