The Market Research industry is finally catching up with Artificial Intelligence

During the past three weeks I travelled 10 time zones east and west of GMT, to present at three different ESOMAR events:

                        1. MENAP Forum 2017 in Dubai on March 22nd
                        2. UK member meet-up in London on March 30th
                        3. LATAM Forum 2017 in Mexico City on April 7th

As a souvenir from Mexico City I brought back a broken foot but …hey….no regrets, it was all worth it.

I have been an ESOMAR member for many years, initially as an agency side executive, and now as an entrepreneur, and overall I mainly have positive things to say about the premier organisation of our industry. I have to admit I was a bit worried at the beginning of this decade, mainly about the pace of adoption of innovation, but I think ESOMAR has now fully recovered and is on the ball again.

This is what I spoke about at the three events:

  1. The integration of social analytics with retail sales reports and brand survey tracking - together with Nielsen
  2. The importance of image processing for theme detection in social listening and analytics
  3. Social media listening case studies in LATAM

In all three of my presentations artificial intelligence and machine learning occupied centre stage. The one thing that makes me even more pleased than getting a speaker slot in those events is that DigitalMR was not the only agency that had something to say about the use of AI in discovering customer insights.

The hardest thing when innovation is introduced in an industry is to educate clients to use it effectively. The inertia that we had to endure during the past few years was relentless. Thankfully, the feeling I have after participating in these events is that there is change in the air. The fact that more people talk about AI now, means that we will finally get some traction in adopting these new methods in mainstream market research. After four years of hard work in doing R&D and running pilots with early adopters, we may be nearing the phase whereby the early majority will start kicking in.

Those of us in this field can use all the help we can get to establish machine learning as an acceptable way of analysing big data and integrating it with surveys and behavioural data. Having said that, we have to be really careful as an industry and set some boundaries that will not allow aspiring tech companies to destroy the image and reduce the value of what market research offers as an industry (to its clients).

The same way ESOMAR once created the 28 questions that a client has to ask a vendor before they engage in online research (using access panels) we now need to define the parameters of acceptable market research standards around social listening, the use of natural language processing (NLP), and by extension artificial intelligence. Here is a list of 20 questions that DigitalMR proposes ESOMAR should use as a starting point to create those standards, in a way that is simple and hopefully easy to understand:

  1. Are the sentiment classifying algorithms based on Natural Language Processing (NLP) linguistic or statistical methods or both?
  2. What is the average sentiment accuracy achievable with the method used?
  3. How is sentiment accuracy defined?
  4. How exactly is the algorithm trained (if one is used) and how long does it take to get to the maximum achievable accuracy?
  5. In what languages can the vendor analyse for sentiment and topics in an automated way?
  6. How long does it take to introduce a new language?
  7. How is noise (irrelevant posts) due to homonyms removed from the data set to be reported on?
  8. Are search terms used or is it an open ended inductive approach?
  9. Are posts weighted according to author influence? If yes, how?
  10. Is the profiling of people who post (by demographics and other variables) available?
  11. How are the harvesting sites selected?
  12. How are comments gauged and classified for sarcasm?
  13. Is the pricing based on the number of search terms researched?
  14. How is the reporting done; what are the deliverables?
  15. If Natural Language Processing is used, are adjectives classified as positive or negative in a library (rule based approach to define sentiment)?
  16. Is the vendor a technology company or a specialized market research agency?
  17. Can specific emotions be detected and analysed? If yes, which ones?
  18. Does the vendor use topic taxonomies to identify discussion drivers? What is their semantic accuracy?
  19. Is image processing for brand logo and more importantly theme detection available?
  20. Can the vendor integrate the harvested data flow with your brand tracking surveys, Nielsen retail reports, or other in-house data sources?

Let us know if you support this initiative and if you have any other questions that you would like to add. As always, feel free to tweet to @DigitalMR and @DigitalMR_CEO.


Why are there no pure DIY Market Research Online Communities?

In 2014, the first time we were interviewed by Forrester about MROCs (Market Research Online Communities), a term they coined, we told them that we were building the first pure DIY MROC platform ever. They were quite impressed and I was too (by their reaction) because I was not aware at the time that none of the known vendors were offering a SaaS that was accessible with zero human interaction. In August 2015, Forrester published “Charting The 2015 Landscape Of Market Research Online Community Offerings” where DigitalMR’s communities247® featured as one of the 14 tools the report was evaluating.

communities247: Private Online Communities by DigitalMR

I find it remarkable that there are only 14 vendors for online communities globally (registering on Forrester’s radar) when at the same time there are over 1,000 social media monitoring tools. I compare and refer to these 2 types of marketing tools specifically because these are the two SaaS products DigitalMR has been focusing on since 2012: listening247® and communities247®. Both will be available as DIY SaaS for market research agencies and brands alike.

For some reason, vendors in the online communities space avoid sharing their pricing plans online. I am not sure if it’s because this is a very competitive sector in terms of prices or because there are so many variations of a service like this that it’s difficult to capture pricing in 3-4 set plans.

SurveyMonkey, which is a great example of a DIY online survey tool, was established in 1999. It took the company 10 years to reach revenues of US$ 28 million; now 18 years later its revenue is closer to US$ 200 million with a valuation of US$ 2 Billion. I think SurveyMonkey despite a horrible brand name - in my humble opinion - became a disruptor by opening up the bottom of the pyramid in terms of new users who could not afford to do surveys up to that point in time. At present there are numerous blue chip customers that use SurveyMonkey for their online market research needs, such as Facebook, Salesforce, Samsung, and Virgin America. SurveyMonkey is now in phase II of the disruptive technologies path that Prof. Clayton Christensen has described in his book “The Innovator’s Dilemma”; they started eroding the market share of the incumbent companies. They are now good enough and simple enough for everyone to use.

DigitalMR will take the step that everyone is avoiding. It could be the most stupid move ever, or the most genius one. I guess we will soon find out. Next week for our presence at IIEX Europe 2017 we will introduce a FREE TRIAL Button on our website for communities247®. There will be no pricing plans to start with, but we will hopefully be able to gauge who is interested in “the SurveyMonkey” of online communities for market research. Another company made this same statement in 2013, but we do not think they have succeeded. Sometimes, timing plays a very important role on the success or failure of a new product. Stay tuned!


10 Predictions for the Market Research Industry
The next 5 years

10 Predictions for the Market Research IndustryHaving the ability to know the future turn of events is a human obsession. Unless we are declared prophets by some religion we are not great at predicting the future using our intuition, dreams, and premonitions, or maybe we are but no one is willing to listen. The human mind can handle linear projections well, but exponential…not so much. Humans usually overestimate the short term and underestimate the long-term evolution and progress. Having this thesis in mind, I will attempt to “call” the linear trend interruption of a couple of slow growth technologies by a “hockey-stick” in market research spend.

We are increasingly using advanced analytics and artificial intelligence to aid our intuition and gut feeling about what comes next. We now have ways to consolidate the wisdom of many humans as expressed on social media and other online sites. The wisdom of the masses, the meeting of minds - especially if they are physically close as in churches, football stadia, or live concerts - has a scientifically unexplainable power. If there is a seemingly plausible explanation for this “power” it lies in the spiritual realm for the time being (as opposed to the scientific).

According to Tetlock and Gardner in their book ‘Superforecasting’ (2015) the most successful approach to forecasting is to combine humans (talented?) + a process (an outside view combined with the inside view and unpacking the original question in multiple questions) + computing.

Without a lot of explanation I am listing my 10 new predictions for market research and customer insights below:

  1. The total spend on social listening and analytics from market research budgets will be US$ 9 Billion by 2020, up from US$ 2 Billion
  2. Social media listening will be about integration with surveys and other data sources instead of a single customer insight source
  3. Market research online communities will replace a lot of the “asking questions” part of market research, possibly 50% of all spend by 2020
  4. Listen-probe-listen-probe using a social listening platform in conjunction with online communities will become mainstream by 2020
  5. Micro surveys that will intercept customers while they perform a relevant action and ask about the experience will grow exponentially by 2020
  6. Traditional customer tracking surveys will become a lot shorter in the meantime, until they will at some point during the next 5 years be replaced by a combined approach of intercepts + social listening + online communities
  7. Artificial intelligence will become mainstream in analysing data for customer insights in the next 5 years
  8. A lot of the market research solutions in existence will become available as DIY in the next 5 years
  9. As a result of point 8 market research will be democratised as a service i.e. become affordable for SMEs
  10. I will chuck this last one in the category of “self-fulfilled prophecies”.  A very powerful notion that has to do more with the persistence and drive of the “prophet” to make something happen. By 2020 DigitalMR will become a global powerhouse in the market research industry or it will be acquired by a global multinational player who will emerge as a winner in the current consolidation wave.

Now you must be asking the question: is this guy a superforecaster (Tetlock & Gardner 2015) according to the definition below?

  1. Outside View
  2. Inside View
  3. Unpack the questions

I will not go through the detailed process on how each of the 10 predictions came to be but I will illustrate it using one example.

Let’s take prediction #1:

A. The Outside View

Outsell, an independent analyst company, predicted the social listening market size to be US$ 5.5 billion by 2020. We know that the human mind is linear and fails to predict the time point of exponential growth. If the growth of social listening was expected to continue to be linear then they would be right.

Innovation in market research historically takes 15 years to become mainstream (examples: CATI, online panels). Social listening started being used by early adopters in 2006. 2020 will be the 15th year since the beginning; evolution of technologies takes a lot less time nowadays, it becomes exponential and ubiquitous a lot faster than in the past (examples: broadband, smartphones, digital content uploads on the web, mobile advertising etc.). This implies that we could see a “hockey stick” before the 15th year.

The total market research market including adjacent companies offering technology solutions for market research is US$65 billion.

B. The Inside View

General Mills, Reckitt Benckiser, Heineken, Vodafone, Diageo and a couple of the largest multinational market research agencies globally all asked DigitalMR to demonstrate how social listening integrates with surveys and other data sources. Successful pilots have already taken place.

These companies are not happy with the accuracy of the social media monitoring tools their marketing departments are already using for other purposes.

They are asking for one social listening tool that can handle multiple use cases, including the one for customer insights.

They are all keen to reduce the spend on monthly customer tracking surveys.

Some other younger companies which are more focused on technology are looking for ways to avoid traditional surveys and use big data in a predictive manner.

C. Unpacking the original question: what will be the spend in social listening and analytics by 2020?

  1. What is the total market size of market research? US$65 B
  2. How much of the total MR spend will not be impacted by the rise of social listening? What is left? Retail measurement, Offline Ad effectiveness, Qualitative research (it will become probing), intercepts= US$ 30 B, US$ 35 B left that can be shifted
  3. What is the current spend on market research and other marketing activities that involve social listening? US$ 2 B
  4. How many years did it take to get to this spending? 11 years. This is an indication that the trend break to a “hockey stick” is close
  5. How many companies that currently spend money on market research will invest in social analytics? Conservatively 70%. These will be the largest MR spenders. What % of the relevant spend will be diverted to social media listening by 2020? Conservatively 15%. This adds up to US$ 5.3 B
  6. How many new entrants will there be in the market research industry from the bottom of the pyramid i.e. SMEs? There are over 10 million SMEs in the US and the UK alone. If 5% of them decided to invest in social listening for customer insights we would be looking at 500,000 companies. How much will they spend per year? DigitalMR is currently a small company and spends about US$ 15K per year on marketing related SaaS. We can assume conservatively that they will spend on average US$ 5,000 per annum. This adds US$ 2.5 B to the estimate of the social listening market for customer insights. For the whole world we can again conservatively add another US$ 1.5 B. The total is US$ 4 B.
  7. As a result the total market is estimated at US$ 9 B.

As ever we are interested in your views and opinions about these predictions. What do you think? Is the social listening and analytics spend about to take off?


A blog post written at 300 km/h

A blog post written at 300 km/h

As promised last week, here I am writing another blog post as I travel at 300 km/hour on the Eurostar towards Brussels - from London - on a Sunday afternoon. I am heading to my second consecutive participation as a speaker at LT-Accelerate; a conference about language technologies, not the usual market research conferences that I attend.

Last year at LT-Accelerate I spoke about rich analytics for social listening and stressed the importance of semantic analysis and accuracy; this year I will be describing what differentiates the more than 1,000 social media monitoring tools currently available out there.

Looking at this from a market research and customer insight perspective, we categorised the social listening tools into three generations:

  1. GEN 1: sentiment accuracy less than 60%, search based topic analysis, limited attention to noise elimination, automated sentiment analysis in usually one or two languages only
  2. GEN 2: sentiment and semantic accuracy over 75% in any language, inductive approach to report topics of conversation, significantly reduced noise (less than 5% irrelevant posts)
  3. GEN 3: In addition to what Gen 2 social listening tools can do, those few that can be classified as GEN 3 can also detect emotions, analyse images in an automated way for brands in terms of theme and possibly sentiment, and they offer guidance for integration with consumer tracking surveys and other data sources and profile users.

If you want to know what generation your current social media monitoring tool belongs to, all you need to do is ask your vendor what is their sentiment and semantic accuracy and whether they can detect emotions and analyse images for insights.

The main reason I go to conferences such as this one is to demonstrate thought leadership in the field of market research and customer insights, with the hope that prospective clients, partners, and vendors will come forward and initiate conversations that could develop to become mutually beneficial deals.

Last year only half of the conference delegates showed up because of the terrorist attack that had happened in Paris. Brussels was on a high terrorist alert that started the Sunday before the conference; the prudent thing to do was to stay at home and switch to a skype presentation as some speakers did. My take on the situation was that a city is at its safest when it is on high alert, so I decided not to change my plans. Indeed as I arrived at the train station last year and on the way to my hotel the streets were deserted, apart from armed soldiers. It was eerie but funnily enough it felt quite safe.

So here I am again this year on my way to the Brussels Central station and in the absence of a red alert due to terrorist threats I sort of feel less safe. I am making a mental note to remain vigilant and pay attention to what is going on around me; look out for any suspicious behaviour in other words.

Enough reminiscence, back to the essence of this post: I am sure there are other meaningful ways to categorise social listening tools and I would be very interested to find out how other people classify them. Maybe a plausible way to classify them is according to the use case of each one. Maybe another is the target customer/department the tool was created for, such as:

  • PR
  • Communications
  • Operations
  • Customer Service
  • New Product Development
  • Customer Insights

In my opinion around 98% of the current tools on the market belong to Gen 1, around 1% belong to Gen 2, and only a handful belong to Gen 3. I would not be the least surprised if the only social listening tool that meets all Gen 3 criteria is listening247®. Clearly, only Gen 2 and 3 tools are suitable and can be used for market research and customer insights. Gen 1 tools would be disqualified from the get-go, if nothing else, due to the noise (irrelevant posts) that is analysed and included in what is reported to the user as relevant.

How do you classify social listening tools? Please feel free to share your approach with me on Twitter @DigitalMR_CEO.

A blog post about…writing a blog post!

I know I should be writing at least 4 blog posts per month, but somehow I only manage to do one. Call it procrastination, call it daily re-prioritisation of tasks, whatever the reason it does not matter. One of my favourite business truisms is: “There are reasons and results, reasons simply don’t count”.

Especially if you think that there is a number of reasons (no pun intended) as to why it is beneficial to write frequently on your company’s website or blog:

1)      You hopefully demonstrate thought leadership in your subject of expertise

2)      You improve the SEO for your website

3)      You can initiate a dialogue with prospective customers or other stakeholders

Reasons 4 and 5 are more personal and can be seen as the icing on the cake: it can be fulfilling and if you aspire to publish a book one day you may discover that you have already written it bit by bit without making a big deal out of it.

My subject of expertise is Online Market Research with special focus on “social listening” and “online communities”. The former is searched for on Google 480 times monthly in the UK only and the latter 390 times – this is what HubSpot says by the way. Both combinations of words are currently on the second page of Google search for DigitalMR. One of the reasons I am mentioning them in this and other blog posts is SEO; I would really love it if we moved up a few places in the Google ranking for these keywords. It could increase the monthly visitors of the DigitalMR website by at least 1,000 if you think that people also use Google in the US and many other countries, to find information on social listening and online communities in the English language.

There is also the issue of the personal brand which apparently is very important for leaders of start-ups. A good friend and advisor told me recently that tech start-ups are the new rock bands. When I was growing up we would look at photos on album covers of rock bands and get inspired, now we look at photos of Zuckerberg and Musk to get our cues on what is trendy.

I was actually planning to write a blog post about the US elections this weekend; instead you are getting a boring introspection. We did a poll on Twitter on October 3rd and the outcome was that Trump received 53% of the votes Vs 47% for Clinton. I did not like the result and I also did not believe it to be honest so we said nothing about it. Now I felt compelled to say: our Twitter poll predicted the US elections result…but I am not going to do it; you see how I did this Smile?

The point is, there is saturation in the media about the subject…. Duh….no one is interested about another Trump story. So now we are getting somewhere; the reason why I am doing an introspection piece is because I want us to be unique and different and offer original ideas that are not recycled a million times.

How am I doing? If you are still reading and you are not my mom or my wife (I don’t think she reads them either) then maybe I am on to something. I will be checking on Google Analytics and HubSpot all of next week to learn something about this style of writing a blog post. I do like A/B marketing tests; I do not know how I will turn this one into a test but I need to figure something out during the next 10-20 lines so that I can offer some take-home value to you the reader.

I am guessing I will write another blog post next weekend on the Eurostar on my way to Brussels for the LT-Accelerate conference. That one will be more about social listening or online communities – see how I did this again? Well don’t get too excited, it is not that easy; it is not enough to mention a keyword several times in a page in order to rank on Google. As a matter of fact, I might be penalised by the Google algorithm if the mention of any keyword is more than 3% of the whole document – so I heard, but you can never be sure with the Google algorithms. The latest is Penguin 4.0 and before that we had Possum and Panda. I may need another few sentences so that the mention of social listening will become 2.9% of the whole post. The previous word was number 749; 3% of that is 21 times; I think we are safe I only mentioned social listening and online communities 4 times Smile.

As always, if you have any comments feel free to share them with me on Twitter @DigitalMR_CEO.