The other 5 reasons why every organisation should build a community online

An online communityIn our previous blog post we mentioned the top 5 reasons why every organisation should build an online community. There are of course more than 5 reasons, so in this blog post we will describe the other 5 , and who knows, maybe we can come up with another 5 in the future :).

Here are the other 5 reasons why every organisation should build and operate private online communities with its stakeholders:

1. Open a window into your customers’ lives

An online community of customers can make the necessary marketing-related information available on tap. It is now possible for all levels of your organisation, not just the marketers, to connect with customers and get first-hand information from them – see them on video and hear them express their thoughts.

2. Increase the number of marketing resources/employees without having them on the payroll
Imagine having an online community of 200-300 customers who can participate in any marketing decision you will ever make. Instead of sitting in a meeting room brainstorming with a handful of colleagues in the marketing department, you can now involve another 300 people in your decision-making process without adding headcount on your payroll.

3. Impress your Board/CEO
Board Directors and CEOs, especially in B2C, love to see and hear a consumer talk about their needs and their products and brands. They are many degrees away from talking to consumers on the street, so bringing the consumers into their boardroom elevates their understanding of the ultimate client and helps them make more informed decisions.

4. Reduce your market research cost
Especially when the target customer is difficult to recruit due to low incidence; owning online communities of customers and being able to invite them to participate in research projects can provide a dramatic saving. For any incidence rate of customers below 10%, a substantial saving can be achieved in the case of needing sample for online surveys and online focus groups.

5. Increase the speed of accessing insights (reporting)
Having a few hundreds of customers on private online communities first of all eliminates the need to find them; that alone takes days if not weeks out of a traditional research project. On co-creation communities, where customers can participate in research as many times as we want them to, not only are we not worried about expert respondents but on the contrary, we want them to become really good marketing employees honing in on their creativity and other skills. Frequent participation and especially designed data collection tools (e.g. short polls) can get surveying time down to 24 hours with a real time observation of the progress. Also, employing the advanced text analytics methods used in listening247 such as machine learning, unstructured discussions on the community wall or a bulletin board can be analysed in real time.

I hope the 5 other reasons make as much sense to you as the 5 main reasons described in the previous blog post. We are very keen to hear your views on other good reasons why an organisation should make it a priority to engage with customers on bespoke online communities.

5 Reasons why every organisation should build online communities

An online communityThis is not just a catchy headline, it is a strong statement, that every organisation should have its own online community

Finding out officially that the online community concept has not yet been embraced or considered by everyone, at least in developed markets, is a bit surprising.  According to the latest Greenbook Research Industry Trends (GRIT) report for Autumn 2014, 56% of all respondents said they are already using online communities. Another 26% stated that a community for their organisation is under consideration, 14% said they’ve had no interest to date or that they are not sure, and  4% claim that they will never use one.

DigitalMR has been developing its platforms for social media research since early 2011; one of these platforms is communities247, with version 3.0 currently in use and V4.0 scheduled to be released in production mode early next year.

Here are 5 main reasons why literally every organisation should build and operate private online communities with its stakeholders:

  1. Agile Engagement with stakeholders is hot!
    ‘Agile’, ‘lean’, and ‘energetic’ - these are image attributes that you definitely want your brand associated with. Being able to open a window into your customers’ lives and inviting them to join the inner circle of your marketing department is extremely powerful. This idea does not have to be limited to customers but can also be used to engage with your employees, shareholders, opinion leaders, journalists, and other stakeholders.

  2. New online collaboration tools open up new possibilities without breaking the bank
    A few years ago, if an FMCG company wanted to conduct ethnography they had to send a camera team to the households of their consumers in order to observe how they use their products. Nowadays, the video & photo diaries tool enables consumers to easily upload video clips or images from their smartphone, tablet or computer. The benefit of online ethnography (or ‘netnography’) is not only financial; the quality and quantity of information gathered has dramatically improved at the same time. This is due to the fact that consumers can upload multiple video clips during a period of time, whereas previously we could only afford to send the camera team to their homes once. Also, the recording is more realistic since  nobody is intruding in their home to record the video clip.

  3. For co-creation and unique insights otherwise not attainable
    Co-creation essentially means, that a company is working with an extended marketing arm by reaching hundreds of customers (or other stakeholders) who operate as motivated employees without having to be on the payroll. The most valuable element that a co-creation community can help produce is digital content to be used for inbound marketing. Connecting the dots by using all possible research activity tools that an online community carries increases the odds  of producing unique insights.

  4. To build a brand ambassador programme
    Amplified customer advocacy or systematised word of mouth are only possible because online communities exist. The co-created content can be shared by the same people who created it as well as other product category influencers on social media. A positive comment about a brand is more believable coming from a “consumer like me” rather than in a TV commercial; amplified customer advocacy is a new mass medium.

  5. More than half of your competitors are already doing it, they must know something.
    We are well into the technology adoption bell curve. It is no longer only the early adopters that are using communities, not even the early minority; we are looking in late majority territory and you are at risk to be labelled a laggard if you are among the 44% who do not have an online community for insights, co-creation and customer advocacy yet. It will soon be seriously uncool to not have your own online community.
     

To be honest I could’ve easily called this blog post ‘10 reasons why every organisation should build  an online community’;  I will save some reasons for the next blog post. If you are among the 56% of current online community users, please do share your experience. We know there is a steep learning curve and it is not always all rosy;  if one is not careful there can be many pitfalls, and if you know of any or if you have any best practices to share, we are all ears. Stay tuned; more to come on online communities soon.

Is there anything left unsaid about social media research and marketing?: Part 3

Sentiment and Semantic analysis

Part 3: Sentiment And Semantic Analysis

It took a bit longer than anticipated to write Part 3 of a series of posts about the content proliferation around social media research and social media marketing. In the previous two parts, we talked about Enterprise Feedback Management (December 2013) and Short -event-driven- Intercept Surveys (February 2014). This post is about sentiment and semantic analysis: two interrelated terms in the “race” to reach the highest sentiment accuracy that a social media monitoring tool can achieve. From where we sit, this seems to be a race that DigitalMR is running on its own, competing against its best score.

The best academic institution in this field, Stanford University, announced a few months ago that they had reached 80% sentiment accuracy; they since elevated it to 85% but this has only been achieved in the English language, based on comments for one vertical, namely movies -a rather straight-forward case of: “I liked the movie” or “I did not like it and here is why…”. Not to say that there will not be people sitting on the fence with their opinion about a movie, but even neutral comments in this case, will have less ambiguity than other product categories or subjects. The DigitalMR team of data scientists has been consistently achieving over 85% sentiment accuracy in multiple languages and multiple product categories since September 2013; this is when a few brilliant scientists (engineers and psychologists mainly) cracked the code of multilingual sentiment accuracy!

Let’s dive into sentiment and semantics in order to have a closer look on why these two types of analysis are important and useful for next-generation market research.

Sentiment Analysis

The sentiment accuracy from most automated social media monitoring tools (we know of about 300 of them) is lower than 60%. This means that if you take 100 posts that are supposed to be positive about a brand, only 60 of them will actually be positive; the rest will be neutral, negative or irrelevant. This is almost like the flip of a coin, so why do companies subscribe to SaaS tools with such unacceptable data quality? Does anyone know? The caveat around sentiment accuracy is that the maximum achievable accuracy using an automated method is not 100% but rather 90% or even less. This is so, because when humans are asked to annotate sentiment to a number of comments, they will not agree at least 1 in 10 times. DigitalMR has achieved 91% in the German language but the accuracy was established by 3 specific DigitalMR curators. If we were to have 3 different people curate the comments we may come up with a different accuracy; sarcasm -and in more general ambiguity- is the main reason for this disagreement. Some studies (such as the one mentioned in the paper Semi-Supervised Recognition of Sarcastic Sentences in Online Product Reviews) of large numbers of tweets, have shown that less than 5% of the total number of tweets reviewed were sarcastic. The question is: does it make sense to solve the problem of sarcasm in machine learning-based sentiment analysis? We think it does and we find it exciting that no-one else has solved it yet.

Automated sentiment analysis allows us to create structure around large amounts of unstructured data without having to read each document or post one by one. We can analyse sentiment by: brand, topic, sub-topic, attribute, topic within brands and so on; this is when social analytics becomes a very useful source of insights for brand performance. The WWW is the largest focus group in the world and it is always on. We just need a good way to turn qualitative information into robust contextualised quantitative information.

Semantic Analysis

Some describe semantic analysis as “keyword analysis” which could also be referred to as “topic analysis”, and as described in the previous paragraph, we can even drill down to report on sub-topics and attributes.

Semantics is the study of meaning and understanding language. As researchers we need to provide context that goes along with the sentiment because without the right context the intended meaning can easily be misunderstood. Ambiguity makes this type of analytics difficult, for example, when we say “apple”, do we mean the brand or the fruit? When we say “mine”, do we mean the possessive proposition, the explosive device, or the place from which we extract useful raw materials?

Semantic analysis can help:

  • extract relevant and useful information from large bodies of unstructured data i.e. text.
  • find an answer to a question without having to ask anyone!
  • discover the meaning of colloquial speech in online posts and
  • uncover specific meanings to words used in foreign languages mixed with our own

What does high accuracy sentiment and semantic analysis of social media listening posts mean for market research? It means that a 50 billion US$ industry can finally divert some of the spending- from asking questions to a sample, using long and boring questionnaires- to listening to unsolicited opinions of the whole universe (census data) of their product category’s users.

This is big data analytics at its best and once there is confidence that sentiment and semantics are accurate, the sky is the limit for social analytics. Think about detection and scoring of specific emotions and not just varying degrees of sentiment; think, automated relevance ranking of posts in order to allocate them in vertical reports correctly; think, rating purchase intent and thus identifying hot leads. After all, accuracy was the only reason why Google beat Yahoo and became the most used search engine in the world. 

The Positive Effect of Negativity

Whenever something unexpected happens in life, some of us pause; we look up and we try to figure it out. Especially if you are curious - like good researchers are supposed to be – discovering a paradox can lead to a hypothesis and looking to prove it can be real fun. When we came across the paradox described in our latest blog post, we investigated and analysed it to death, and then we started thinking about similar cases that may support our hypothesis i.e negativity under certain circumstances may have a positive effect.

Click here to download a free eBook on The Positive Effect of Negativity

What seems to have happened in the case of Coca-Cola, is that passive social media users saw the racist comments towards the ad and decided to come to its defence. They expressed their dissatisfaction with the reaction of the people posting negative comments using very strong language. Indirectly, these negative comments about the negative posts “attacking” Coca-Cola can be considered as positive for the brand; in simple terms negative about the negative equals positive - imitating how multiplication works in mathematics.

Is it possible that we are looking at a new marketing phenomenon applicable both in business and in politics on how to harness ‘The Positive Effect of Negativity’? In a nutshell, every brand that would like to stir some noise around it makes a controversial statement with its communications - but hopefully controversial only for a small and evil group of people. When the minority group reacts against the brand, the passive and sleepy majority then wakes up and defends the brand against evil; the positive effect of negativity may simply be turning apathy into action.

To find out more, download our eBook on ‘The Positive Effect of Negativity’.

The Amazing Paradox of Negative PR for Coca Cola

Most people would agree that any PR is good PR; however, I don’t think I was the only one thinking that Coca-Cola did NOT see it coming on February 3rd - the day after the Superbowl final. I kept thinking that the brand is damaged, that sales would be affected negatively, and that some heads are probably rolling within TCCC (The Coca-Cola Company) in Atlanta. A simple piece of pre-advertising research could have told them that some people in the US are so patriotic, or perhaps we can even use the word racist, that they felt offended by the fact that people of other ethnicities were singing ‘America the Beautiful’ in their own language as opposed to English. All hell broke loose on Twitter and other social media platforms immediately after the ad was aired and continued for the following days and weeks.

Click here to download a free Coca-Cola Superbowl ad case study

We had initially harvested the posts with the intention of publishing a blog post showcasing eListen’s sentiment accuracy of over 85%; however since this wasn’t a paying project it kept falling to the bottom of the priority list to process, analyse, and create some content around it. Our thought was to use the approach “sales by fear”; we wanted to tell all the brands out there that they need to be constantly “listening” to online chatter about themselves and their competitors in order to be able to handle situations as they arise. They should not allow their brands to be at risk of negative PR and loss of brand equity, something potentially catastrophic in real business terms.

According to DigitalMR’s findings during the 8 days prior to the Superbowl, there were 139,997 posts about Coca-Cola in the English language; 22% Negative, 7% Positive and 71% Neutral. During the 8 days following the airing of the ad, the number increased by 169% to 376,382 posts. The interesting fact here is that although the number of posts increased by 169% after the campaign airing, the amount of negative posts still accounted for 22% of the total while positive posts jumped to 51%.

If you want to find out more about what really happened, and what the actual effect of the campaign was, please click here to download a slide deck with our findings, and stay tuned for the upcoming eBook on ‘The Positive Effect of Negativity’.