Data vs Insight: The Albatross Around the Marketer’s Neck

We have so much data at our fingertips. Every touch, interaction, click, email, webpage view. It all results in data. Even when we walk from one room to the next our phones are counting the steps, movement, changes in latitude and longitude. We are measured to within an inch of our lives.

Some of this data is captured and reported back to cloud based servers scattered across the globe. Some of it isn’t. But do we know? Do we care?

I was speaking with John Dobbin yesterday about the Data Paradox. We have more data than ever before, but less understanding of what to use it for. We spend our time analysing dashboards and combing through spreadsheets in search of that elusive insight. Sometimes as a marketer I feel like Coleridge’s ancient mariner:

Water, water, everywhere,
And all the boards did shrink;
Water, water, everywhere,
Nor any drop to drink.

Data visualisation goes a long way towards solving this challenge. Done well, it can bring your data to life – tell a story – and foreground important details. But with almost every visualisation I see, I am always asking myself, “why”. Why is this important? Why did a change occur? Why didn’t a change occur?

Take a look at my recent TwitterCounter graph below. It shows follower/ following counts over the last month. You can see there are a couple of spikes in terms of follower numbers. But you can also see that “following” numbers remain on an even trajectory. Just the simple act of looking at this graph reminded me of the actions that I had and had not taken over the last month. It made me check back to see what I was doing on March 7.

And on March 11, clearly I did something to arrest that growth. But the following week I was growing again. Not as steeply, but strongly.

twittercounter

Correlation vs Causation

Again the question of “why” raises its head. What I am interested in is not the correlation but the causation. At the book launch of Martin Lindstrom’s new book, Small Data, he suggested that it is the small data that drives causation and that big data shows the correlation. So with this in mind, I looked to the small things.

  • Ahead of the first spike in follower growth I started using Meet Edgar to more consistently tweet. Prior to that it was randomised and scheduled or ad hoc. It was not a function of what I was saying, but the fact that I was saying it.
  • The second spike built on the earlier week but benefited from my appearance on DisrupTV with GE’s Ganesh Bell and Constellation Research’s Guy Courtin.

While the big data revealed the trend and the results, it was the small data. The personal data. The insight, that actually revealed the causation. As Martin Lindstrom suggested, and as I have written previously, small data – the known unknowns of the marketing world – tell the story we are waiting to hear. The question is whether we are listening for a story or searching for data.

The Price of Marketing is Innovation

Marketing teams everywhere are experiencing a profound disruption. It’s a change in thinking, planning, analytics and platforms unlike anything that we have experienced previously. And while the changes happening to us as marketers are unsettling, far more troubling are the changes happening around us as marketers, business people and consumers. We are living on the pinhead of a transition that is sweeping all before us and swallowing the past as it goes.

Living in a platform age has changed the dynamics of our lives. What was personal has become professional and what was “work” has become, well, less clear. Less defined. After all, we can now “work” from home, from a coworking space or shared office. Even a cafe around the corner from your home can serve you VPN access with a steaming hot cappuccino. We are an always-on, digitally connected, wifi enabled workforce that can transform from knowledge worker to connected consumer faster than Snapchat can forget that selfie you posted to your network of faux friends and friendly foes.

And the platforms have come a long way, taking advantage of four transformative technologies – social, mobile, analytics and cloud. The SMAC model. For years, technology companies have known about the power of platforms – using SMAC to create competitive advantage and commercialising the value across networks. Startups have known this too – though often without clear and incisive strategy. They’re too busy moving quickly across the platforms to harness their potential for scale.

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But this is changing. All businesses are changing.

These days, any business can become a technology business. What was once my consulting business – Disruptor’s Handbook – has become a technology business. We are deeply technology enabled – from CRM to lead and opportunity nurturing, communications management, planning, collaboration and execution right through to business analytics and financial management. The intellectual property that we have created has been downloaded thousands of times and is being put to use in 25 different countries including the UK, China, South Africa, South Korea, Japan, India and Mongolia.

This can only happen because we have embraced the SMAC model. We have apps in the cloud, integrated using pieces of string, chewing gum and a raft of zapier zaps, API calls and pre-made plugins. It means we rely on a dozen services rather than a single suite, but it holds together and works almost flawlessly. Until it doesn’t. But it provides a scale that would otherwise be difficult to achieve without a significant technology budget.

And if we can do it, you can too.

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Swallowing the past

Just when you start to feel comfortable with your technology choices, the rubber bands and sticky-tape that you use to hold it all together, the worst possible thing happens. Well not exactly the worst, but modern marketing’s closest equivalent. A new technology is released. Or an upgrade or a patch. And this new thing is so bright and shiny, you feel like Cory Hart in a film clip straight from the heart of the 1980s. You can’t help but to download it. Sign up. Trial. Share it with friends and colleagues.

And this one new thing makes you question all that has gone before it. Imagine Facebook before it bought Instagram. Or Google before it bought Urchin. These companies are moving so fast, transforming their user experience and brand promise so quickly that we hardly remember what life was like before the change occurred. These platforms are swallowing the past moment by venture-funded moment.

But where do we start? In the marketing technology field alone, Scott Brinker estimates that we are dealing with over 2000 technology choices across almost 50 category areas. In each of those categories we face a dazzling array of choices, capabilities and technologies. So much so, that we often elect to do nothing. As marketers we are suffering from one of our own invented marketing conditions – decision paralysis. We refuse to take a step forward out of a fear of being wrong-footed.

Yes, the future is bright and it is long, yet we are living a constant present.

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Marketing technology – it’s not a footstep but a journey

Traditionally, marketers have always had their eye on the customer. But in the rush to transform their approaches, update their skills and stay ahead of the competition (all while still delivering ROI), many of us have been blinded by the technology light. The problem is that this is not a light. It’s a train and it’s heading in our direction. Marketing technology has put us on a set of rails that are almost impossible to escape from.

But there is a way.

Rather than following in the digital footprints laid out in front of us, we must consciously choose an alternative – the customer journey.

When we start with our customers and their journey it changes the game for us. Rather than generating campaigns, leads and opportunities, we are seeking to understand our customers’ needs, expectations and path to purchase. It’s less about how we sell and more about how they buy. And when we understand this, we can then select the technologies that help us deliver that experience.

How do we do this?

Clearly it requires new thinking and new skills.

Agile marketing and the new world order

In many agencies, agile marketing has been the order of the day for sometime. Building on the old “traffic management” model popularised in publishing houses, digital agencies have been adopting agile methods and approaches to deliver their marketing solutions for years. But in this world of constant change – with a need to swim upstream to where the new sources of business value lie, client side marketers are having to adapt their own ways of working. Out are the old metrics and in are the new. Same with skills. Creative. And technology. Many of our marketing platforms have already been superseded – yesterday’s cutting edge marketing cloud is already burning like acid rain.

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Our increasingly complex world is expecting increasingly complex solutions. We can’t just work in broadcast or print. It needs to be omni-channel. Mobile. We need the best of social and the power of analytics. We need predictive modelling and on-demand forecasting. There are so many new acronyms that we need a new urban dictionary just to keep up. I have been exploring these topics on the Firebrand Talent blog – seeking to match the changing landscape a framework for marketing renewal.

In fact, I am finding my work in innovation is meeting my work in marketing. They complement and reinforce each other. And in the best instances they catalyse and accelerate each other’s effectiveness.

These days the modern marketer has no choice but to create a new world order. Gone are the certainty of ratings and public statistics. Gone are the guaranteed budgets and elastic ROI figures. In are hard numbers, data analytics and real time bidding. It’s like working with an armful of tactics while building strategy on the fly. We can do it, but we do need to ask – is it best for the business and best for the customer? Is it brand-wise?

The time has come to shift not only our thinking but our practice. It’s time that we recognise that customers are not going to buy something just because we interrupted their continuously connected life with the right offer in the right place at the right time. We need accept that we need to build new products for new conditions, not just create new campaigns to spruce up a tired offering. It’s time we stopped talking about “agile” and started “being” agile. We need a marketing system for the disruption that we are all living.

But what is it going to cost? I hear you say.

It’s not a cost. Modern marketing is an investment. And innovation is the price of getting a seat at the customer’s table.

Forget Data. Let’s Talk Revelation

I love data. I love the way that it can be collected, crushed, crunched and reported. I love its beautiful, malleable nature and the way that it sticks incongruously to information.

I particularly love the way that data can be wrestled into shape to yield an answer. Years ago, I was able to accurately predict a corporate takeover through the harvesting of different types of web data, analytics and a spot of digital snooping. But what I found was not data – or even a series of data points. What I found was a revelation.

These days I am constantly reminded of the gulf that exists between data and analysis, analysis and insight and insight and revelation. We have “fact checking” websites, big data repositories and infographics proclaiming the best practices for everything from walking dogs to the time to send emails. We are swimming in a sea of data without an insight to save us.

We think – as marketers, or business people more generally – that data will give us the answers. But this is incorrect. It will only point us towards more questions that need to be asked. This is why switched on marketers are adapting the techniques of “growth hackers” from the startup world. Growth hackers have learned that you can use data to test, experiment and improve your marketing – and that this is a never ending cycle. A constant irritation and challenge. It’s also a necessary part of proving value to your customers.

Growth hacking puts data in its proper place. As yet another point to consider when trying to deliver commercial or social outcomes for a brand. But it’s not the only one. It’s not even the most important one.

This great video featuring Richard Huntington, Director of Strategy at Saatchi & Saatchi makes the point that what we are seeking is not data. It’s revelation. And in too many instances we stop at data. Or thread-bare insight. Falling short of revelation. And that is doing no one any favours.

As Richard says at the end of the presentation – we have to remember which business we are in. I will leave him to remind you which that is.

Big Data and the Trust Paradox

We have all become blasé about the information that we share on the internet. We openly tweet, share updates, create photos and post images about where we are, what we are doing and who we are with. We carry our mobile phones with us everywhere – and have become so reliant upon them that we have had to name a condition for the state of anxiety we find ourselves in when we leave our phones at home. It is “nomophobia” – literally the fear of having “no mobile”.

And just as our internet connection is “always on”, so too is our phone. And being always on, it’s always collecting, sharing and posting data about us. Even when it’s sitting “idle” in our pockets it is triangulating our position, beaming our latitude and longitude to satellites, connecting to wifi hotspots and cellular phone towers. Many of the apps that we use also collect and share our location – some are obvious like Google Maps and Facebook. Others not so. But it’s when we start using the phone, that the data really explodes.

The following infographic is now quite old, being originally published in 2010. It shows the “meta data” – the hidden data that is relayed along with every update that you make using Twitter. It’s not just the 140 characters of your message, but hundreds of additional characters that accompany your message, including your:

  • User name
  • Biography
  • Location
  • Timezone
  • Follower / following statistics.

And more. So much more.

AnatomyTweet

Trading privacy for convenience

The accepted wisdom is that users of these services are knowingly trading privacy for convenience. The reality is vastly different. After all, when using the internet, we are not working in full knowledge. In fact, our understanding of what we are doing, how much information we are revealing and where our data goes is extremely limited. And even when we choose to share location information with an app or when we accept notifications, chances are that we will forget that consent has been given. Or the context in which that consent was given will become lost in the daily grind of our busy, connected lives.

This plays well for those platforms that collect, harvest and sell the data of their users. In fact, it’s one of the business models that many startups rely upon – data collection, harvesting, sale and exploitation is the name of the main game. But there is change in the air, and we can expect that these business models will increasingly come under greater scrutiny and pressure. A 2014 an EMC poll revealed that only 27% of those surveyed were willing to trade their private information for a more convenient online experience. And over half (51%) straight out said “no”. Moreover:

The majority also believed “businesses using, trading or selling my personal data for financial gain without my knowledge or benefit” were the greatest threat to their online privacy.

These beliefs and expectations were further reinforced in the Pew Research Center’s Future of Privacy report, where “Some 55% of these respondents said “no” they do not believe that an accepted privacy-rights regime and infrastructure would be created in the coming decade”.

Yet despite an inherent and ongoing suspicion of corporations and governments, the Edelman Trust Barometer for 2016 reveals that the general sense of trust is improving. Edelman’s research describes a well educated and well-resourced segment of the population (approximately 15%) as the “informed public” – and measures trust in the wider population as well as this narrower segment. To qualify for the segment “informed public”, people must be:

  • Aged 25-64
  • College educated
  • In the top 25% of household income per age group in each country
  • Significant consumers of media and report high engagement in business news.

This also means that the “informed public” would be considered a “tech savvy” audience.

While trust has grown overall, it has accelerated faster between 2015 and 2016 in the “informed public” segment. And this is what makes this report so interesting. Despite a wide and growing concern around big data, meta data and data analytics, those who are MOST LIKELY to know and understand the use to which their data will be put, are reporting an improvement in their sense of trust.

And it is this “Trust Paradox” which offers both hope for business and a warning. For while trust has been improving, business and government is only as trusted as the last security breach or unexpected outage. The IBM/Forbes’ Fallout Report estimates that “lost revenues, downtime and the cost of restoring systems can accrue at the rate of $50,000 per minute for a minor disruption”. A prolonged problem would take an even greater toll on brand reputation and business goodwill.

The risk of a breach or outage, however, is not shrinking but growing, thanks to the proliferation of “shadow technology”, expanding supply chains and growing online activism. And as digital transformation continues to take on an ever greater role in customer experience, the potential for consumer impact and reputational damage also grows.

John Hagel suggests that as brands work towards a “trusted advisor” status, that they will have a “growing ability to shape customer purchasing behaviour”. But brands will only have this luxury while the Trust Paradox works in their favour. At present, the Edelman Trust Barometer suggests the balance of power remains with our peers. We trust them more than anyone else. And that means securing or “scaling trust” (using John Hagel’s terms) remains our real challenge in the years ahead.

Periscope Captures from the ADMA Global Forum

Live streaming using apps like Periscope and Meerkat have revolutionised conferences of all kinds. No matter whether you are hosting a small lunchtime gathering of friends, colleagues or experts, or attending a massive conference, these easy-to-use apps allow you to share what you are seeing with the wider world. Or at least those who follow you on social media.

With this in mind, I thought I’d put both Meerkat and Periscope through their paces at the ADMA Global Forum. The ADMA Global Forum brings the world’s leading data driven marketers together to share insights, best and emerging practices, case studies and strategies. This year, there is strong representation from technology firms with good stories to tell. Oracle, IBM and Marketo are represented. Facebook is too. I also dropped by the stands of IVE, Minfo, and others. This year is an improvement on last, but there’s more work to be done on their exhibition stands and their ability to talk to marketers on their own terms. If you have a tech brand needing to talk “marketing”, then maybe we should talk too.

I live streamed and recorded a number of sessions and embedded them below. Tomorrow I will go deeper. Do some interviews. Chat with the teams on the exhibition stands and some of the audience. Let me know what you’re interested in and I will see who I can talk to.

@AndyVen from TheOutNet

Marketing Automation with @Missguided

Case study from @Missguided

Case study from Bosch

Case study from Regions Bank

Content Strategy from @TheOutNet

Case study from Getty Images

Personalisation strategy from Sitecore ANZ

Five Insights into the Psychology of Twitter

Statistics and sampling are an amazing thing. Even if, like me, you have a healthy scepticism about the way that data is analysed and interpreted, it is difficult – if not foolhardy – to downplay the inevitability of data. Just look at the various disputes around the veracity of climate change – where statistically irrelevant interpretations have derailed important decisions, changes and commitments. Eventually, even the hardiest data curmudgeon will need to yield to the truth of the climate science data – perhaps only as their seaside apartment is swept into the arms of the sea. For though there may be outliers and anomalies in the data, sampling – where carried out correctly – can yield tremendously accurate insight. As Margaret Rouse explains on the TechTarget website:

Sampling allows data scientists, predictive modelers and other data analysts to work with a small, manageable amount of data in order to build and run analytical models more quickly, while still producing accurate findings. Sampling can be particularly useful with data sets that are too large to efficiently analyze in full — for example, in big data analytics applications.

And it is sampling that makes Twitter one of the more fascinating social networks and big data stores of our time. While Facebook grows its membership into the billions, its underlying data store, its connection and interaction architecture and its focus on first tier networks also limits its capacity to operate efficiently as a news source and distribution network. Twitter on the other hand, with its 200+ million members, provides a different and more expansive member engagement model.

During our recent forum presentations on the voice of the customer, Twitter’s Fred Funke explained the view that Twitter was “the pulse of the planet”. Using tools as simple as Twitter search or Trending Topics, Twitter users can quickly identify topics that important to them – or to the broader local, regional and global communities. And, of course, with the new IBM-Twitter partnership, there are a raft of tools that allow businesses to go much deeper into these trends and topics.

In doing so, however, we have to ask. What are we looking for? What information will create a new insight? Which data points will reveal a behaviour? And how can this be framed in a way that is useful?

Five Buyer Insights that Drive Engagement

Just because interactions are taking place online doesn’t mean that they occur in isolation. In fact, our online and offline personalities are intricately linked. And as the majority of our digital interactions take place via text, linguistic analysis will reveal not only the meaning of our words but also our intention. Some things to look out for and understand include:

  1. Buying is an impulse: As much as the economists would like to believe we act logically, we know that buyers are emotional creatures. We buy on whim. On appeal. On impulse. And there is no greater impulse these days to share an experience (good or bad) via Twitter. Look particularly at the stream for comments tagged with #fail. It is full of opportunity for the responsive marketer keen to pick up a churning customer having a bad customer experience.
  2. The customer journey is visible: While we are researching our next purchase, digital consumers leave a trail of digital breadcrumbs that can be spotted using analytics software. For example, we may tweet out links of videos that we are viewing on YouTube, share blog posts related to our pre-purchase research and even ask directly whether a particular product lives up to the hype. Just take a look at the #lazyweb stream around the topic of Windows10.
  3. Understand the pain to optimise the opportunity: When engaging via social media, it is important to understand the challenges or “pain points” that your customers (or potential customers) are facing. Rather than spruiking the benefits of your own products, focusing on an empathetic understanding of your customer’s needs more quickly builds trust and is grounded in a sense of reality. The opportunity with social media is to guide the journey, not short cut it.
  4. Case studies build vital social proof: No one wants to be the first to try your new product. Showing that the path to customer satisfaction is well worn is vital. Use case studies to pave the way.
  5. We buy in herds: Mark Earls was right. Not only do we want social proof, we prefer that proof to reflect on our own sense of belonging to a group or movement. Remember that we go where the other cows go, and structure your social media interactions accordingly.

The folks over at eLearners.com have put together this infographic on the psychology of Twitter. They suggest that we tweet for love, affection and belonging. It may be true, but sometimes we just also want to vent. And every vent is a market opportunity.

psychology of twitter

Forget Big Data, It’s Time for Big Narratives

It is easy to get excited about big data. After all, it’s lots of small pieces of data woven together into a patchwork that stretches our imaginative capacity. Just think, we’re creating more data every two days than was produced from the dawn of civilisation up to 2003 (or so Google’s Eric Schmidt claims). That means that every photo, status update, movie, podcast, purchase, share and any other form of interaction that we make on a digital forum – PLUS all the metadata of that interaction – is adding to a massive pool of data that sits like a great digital artesian basin underneath our digital experience.

The question about all this data, however, is what do we do with this big data? Sure we can mine it, connect internal and external data. We can use it for retargeting. Or forecasting. Or analysis. We can put it into charts and infographics and in doing so, add our own efforts to the big data explosion. But it feels like we are just scraping the surface. It feels like we are in our digital infancy when it comes to big data.

But there are a few companies who are innovating on the edge and taking a different approach. For these companies, big data is just a means to an end. The real value is not in the data but in the capacity to tell stories with that data. It’s the realm of big narratives – and it is as exciting as it is terrifying.

The team at Narrative Science have been focusing on machine learning and linguistics for some time. Their natural language generation platform takes big data and applies artificial intelligence to it in such a way that reports are not just visual but contextual. That is, there is the result and the reasoning all-in-one report.

I have written about QuillEngage previously, the platform that turns your Google Analytics data into a summarised report email. So I was interested to see what would come out of their new Twitter report.

twitter-quillengage

Based on an analysis of my Twitter traffic and the traffic of my recent followers, Quill examined around 13,000 tweets to produce the report. Most interesting to me was the analysis of my own tweets and the topics that “my community” engage in. While my follower numbers and ratio put me in the “99th percentile of Twitter users measured by followers”, the report provides little in terms of suggestions for growth / improvement. But it does confirm what I suspected. And in most cases, that’s how many marketers are using big data at present – as a sense check. A validation.

But as technologies like this get better, more automated and programmatic, there’ll be less sense checking. Less validation. And more action. It’s just that that action won’t be taken by you or I.

Voice of the Customer @ #IBMconnect

The IBM Connect roadshow moves from Auckland to Sydney and then to Melbourne over the next few days. Come along and learn how you can turn data into business value.

The Known Unknowns – Small Steps Big Gains with Watson Analytics

Reports that say that something hasn’t happened are always interesting to me, because as we know, there are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns – the ones we don’t know we don’t know.
Donald Rumsfeld

My morning starts with a river of data. First up, there is email – a quick run by the inbox alerts me to urgent issues, questions, client inquiries and news. Every email I open, every link that I click and every article that I read is marked, tagged, tracked and collated. And then it’s over to LinkedIn’s news feed to check what is happening in the industries I care about. Having built a substantial network of well-connected and insightful connections over the years, I get a very quick sense of what is trending globally, what is vital locally and what needs to be reported or responded to. Finally, I switch to Facebook. I am blessed with opinionated and smart friends who share and increasingly, the richness and quality of news and insight available through that network is out-pacing all other channels.

But what am I doing here? I am working with Donald Rumsfeld’s mantra. I am looking to these networks to tell me the things that I don’t know that I don’t know. Essentially, this data is helping me look beyond my radar.

The same approach can be applied to marketing. In fact, for marketers to remain relevant and responsive – we need to be looking beyond our own radar.

For as long as marketers have been marketing, we have used media to reach our customers. We’ve equipped our teams with megaphones and messages and marched them to the perimeter of the business compound. To reach our customers, we buy and create media – after all, as the adage says, “fish where the fish are”. But this is the inside-out marketing model from the 20th Century – and social media has turned it inside out.

Turning to sites like Twitter or Facebook – or even LinkedIn for the B2B marketer – can feel like facing a firehose. The torrent of information coming through is astounding. Just take a look at the recent social media statistics for Australian audiences:

  • Over 13 million using Facebook
  • 13.5 million using YouTube
  • 2.5 million using Twitter

But it’s really not the big numbers that are important here. It’s what you do with them.

The known unknowns of our customer data

Just as I do each morning, marketers need to be thinking selectively about their customers. Rather than aiming to speak – or “connect with” all 2.5 million Twitter users in Australia, why not start somewhere easier? Why not start with the “known unknowns”? Why not start by figuring out WHICH of our customers are using Twitter or Facebook (ie a lot of them), and improving our understanding of those people?

Most modern CRM platforms have fields that allow you to collect the Twitter handles or Facebook profiles of your customers. Why not start by understanding how many of your existing customers have this information included in their profile? This gives you your known unknowns:

  • Run a report on your completeness of social media profile data in your database
  • Use Facebook custom audiences to match Facebook profiles to your existing email database
  • Do some profile matching via Twitter to do the same
  • Run an email campaign asking for that one additional piece of information. Provide a useful incentive. Make it worthwhile.

For most organisations, taking these small steps would take less than a day. And it paves the way for much deeper exploration.

Combining Voice of the Customer and Analytics as your over the horizon radar

Once you know who your customers are on social networks, it opens the door to a much richer experience for both you as a marketer and your customers as consumers. And what you’ll find on social networks is not the well-manicured conversation of corporate marketing – you’ll find the very direct “voice of the customer”. Generally, however, our “social listening” platforms are built around our own keywords. Our products. Brands. They are only sometimes built around understanding our customers pain points, needs and expectations. This means we are again working from the inside-out – working with the known knowns.

Thankfully, powerful natural language processing is beginning to provide the analytics horsepower we need to decipher social streams. I have explained previously about the way that IBM and AusOpen collaborate to transform customer experience at the Australian Open Tennis events – but analytics is no longer the domain of big business. With platforms like IBM Watson now available at an affordable rate (starting at around $50 per user), you don’t need to be “Tennis Australia” nor a data scientist to understand what’s going on with your market. You just need to understand your business.

Take a look at this video to see how you can use Watson and Twitter data to analyse retail sales. Look at the way that the language in the real time reports is structured around the way that marketers work. Rules are setup and then data populates accordingly. But most interestingly, because Watson works with natural language – it works with the language of the marketer as well as working with the language of the customer.

For marketers, this means that Watson does the hard work of identifying the most interesting facts contained within your data sets, letting you focus on making the right decisions about what happens next. For example (at 2:13), “sales by state” is flagged. Watson chooses the best representation of the data (in this case, a map) but also provides a “ribbon of data” that can be used to interrogate and analyse at a deeper level. Typing in a search related to what you need to know (eg “tweets by hashtag”) turns that data into a report that lets you see immediately what happened to your sales data and why.

Suddenly that river of Twitter data becomes understandable. A connection can be made between your business results and the social media data coming from a particular channel in a particular location.

And in case you need to tell the story of your digital marketing and your analytics to your executive team – or to your customers – with a few clicks, the visualised data can be compiled into ready made infographics. Now you not only have a custom radar to understand your customer – you can link your customer and business value together. Will this make you a better marketer? It will certainly make you more relevant to your customer – and that is a win all around.

Marketing and Dating: How to Get a Date by the Numbers

Dating is big business. There are generic dating sites designed to help you find a date, a life partner or someone just to hang out with. There are also incredibly focused dating sites that are designed to introduce you to other people who have the same particular passions and interests as you. Maybe you are looking for a “sea captain” or perhaps you just hate it when Movember finishes and need to sate your passion for the tache. Whatever the case, if you look hard enough you’re bound to find a dating site designed just for people like you (yes, you crazy cat lady).

In many ways, the challenge of dating is the same challenge that marketers face. We’re all looking for that one-to-one connection – though often we struggle to a way to meet and start a conversation. In both cases (marketing and dating), digital disruption is creating both opportunities and challenges. And at the heart of this is data.

Inga Ting reveals that what we say in our dating profiles and what we want are often completely different. Dating sites – just like data-driven marketers – are less interested in “stated intentions” and more interested in actual behaviour. By looking at online behaviour – the things that we like, connect with, share and return to – marketers can adjust their profiling to reach and more deeply engage potential customers. This algorithmic approach relies not on focus groups and market research but on an adaptive approach which operates between your stated profile (self designed) and the actions you take online. In the world of online dating it means operating in-between spaces:

Behaviour-based matching is adaptive. It compares what you said you wanted with how you behave to work out things you might not even know about yourself.

For example, you said you wanted a partner with a steady income but you keep messaging “pro-bono computer game testers” and “freelance writers”, so the algorithm changes its recommendations.

Our profile

But, of course, while there can be volumes of data about ourselves online – we are also highly visual. The rise of photo based apps like Tinder for example shows that sometimes dating (and even marketing) is only skin deep. Relying on your photo and your location information, Tinder matches people based on whether they are close and interested (you swipe a prospective date’s photo to the left to reject and to the right to connect).

For those who are serious about dating, perhaps a single app is not the answer. The “multichannel” approach that works for marketers may yield better results. Take for example, the data from Axciom’s infographic (ht Will Scully-Power) that reveals that, in Sydney:

  • Single females outnumber males at all ages except the 18-24 age group
  • Potts Point is home to the most singles
  • Wine enthusiasts are most likely to reside in the Eastern and Inner West suburbs

If you were a male in the highly competitive 18-24 age group, a multichannel (or omnichannel) marketing approach to maximising your chances would include:

  1. Establishing your base profiles on high traffic sites
  2. Create a profile image that shows your passion for fitness and interest in fine wine (please be tasteful)
  3. Spend time in cafes in Potts Point using Tinder

Of course, you could pepper your profile with quotes from Shakespeare, but that may be overkill. Remember, that the algorithms will override your stated profile anyway – so your true intentions will always be revealed in the data – based on who you swipe right and who you swipe left, who you message, like and connect with. And like all good marketing, the question comes down to ROI, engagement and outcomes. I hope you get your algorithm right!

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