Beating the Kobayashi Maru – or the human vs machine experiment with Watson

“I don’t believe in no-win scenarios.” (James T. Kirk, Starship Captain)

When you are a strong believer in datadriven decision making, building strategies on real insights, and always sticking to facts rather than fiction – it’s a hard blow when one of the world’s leading artificial intelligence systems tells you, that you are not a nice person. It’s based on data – so it’s a fact.

Many industry leaders have evangelists who are excellent presenters and subject matter experts. It’s always a privilege when you get a chance to interview an evangelist. I met IBM’s Rashik Parmar, Watson evangelist, at IPExpo Nordic a few weeks ago.

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Source: IBM

There is so much potential for big data analysis and the learnings and insights we gain, from combining the many available sources of accssible data to draw new conclusions and find answers. That’s basically what Watson does. And then makes the logical connections. Simply put.

IBM developed a small demo engine that would analyse your Twitter personality and generate those awesome charts we all love; and few of us know how to interpret. It was reassuring to see what a nice guy President Obama is on Twitter. And my friend, Rashik, had a similar profile – so all good.

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Source: IBM’s demo app TweetMeWatson

Lucky for me, we couldn’t make it work for my profile until I got home. When I ran it, I found out I was

“Inconsiderate and a bit shrewd”

I will spare you the rest. Either I am very delusional about how I express myself, or there was something fishy going on here. But it’s based on data! It has to be true!

Before digging a hole in the garden to hide from the world – or the equivalent: deleting my Twitter account – I decided to think it through. What was Watson picking up on, what were the actual parameters used?

The Big Five (FFM) Personality Traits

Watson is grouping our personalities according to the Five Factor Model (FFM) Wikipedia explains:

The Big Five personality traits, also known as the five factor model (FFM), is a model based on common language descriptors of personality (lexical hypothesis). These descriptors are grouped together using a statistical technique called factor analysis (i.e. this model is not based on experiments).

This widely examined theory suggests five broad dimensions used by some psychologists to describe the human personality and psyche.[1][2] The five factors have been defined as openness to experienceconscientiousnessextraversionagreeableness, and neuroticism, often listed under the acronyms OCEAN or CANOE. Beneath each proposed global factor, a number of correlated and more specific primary factors are claimed. For example, extraversion is said to include such related qualities as gregariousness, assertiveness, excitement seeking, warmth, activity, and positive emotions.

220px-francis_galton_1850s It all sounds very reassuring, the term “Lexical Hypothesis” makes sense –  it was analysing words. This is a principle which was developed by British and German psychologists to identify a personality characteristic. It was used to determine risk of mental illness or criminal behaviour. Invented in 1884, by the way, by Sir Fancis Galton – a stern looking fellow.

But something as elusive and intangible as the human mind is so very hard to classify and illustrate in data points and charts. By creating a lexicon of words and adjectives that at the time were considered to be indicators for certain behaviours, they provided a tool to build profiles – and categorise people based by their choice of words.

Note that the method has also received a lot of criticism – many of them quite reassuring when you are on the receiving end of this exercise. Read more here. 

Phew – that means I can still be a nice person, just not when I tweet. Or speak.

It seemed safe to climb back out of the hole in the garden and meet the world face on. But knowing now what triggered my unpleasant profile, I decided to challenge Watson to a duel.

A duelling experiment

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@echrexperiment is the experimental Twitter profile where tweets were worded more carefully, where people and followers were thanked and nothing bad was happening in the world. No politics, no injustice, no gender inequality, no discrimination. And lots of cats.

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After three weeks, I was a much nicer person. The traits that I seem to be exploiting negatively in my original profile are now contributing to a positive image.

Suddenly, uncompromising was a good thing.

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“In academic vernacular, you cheated”

Like Captain James T. Kirk in Star Trek challenging Mr. Spock’s designed program, I cheated to win.

Most of my tweets were carefully drafted using positive semantics but remaining true to my usual topics of interest. I was not trying to be someone else, just focusing on being nice. Here’s a list of the parameters I introduced to make Watson love me more:

  • Following back – anyone who followed me, unless an obvious business account or egghead, was followed back as soon as I spotted them.
  • #FF – sometimes I used the FollowFriday hashtag to thank select people. It generated some nice interactions even between those mentioned, so I grouped them into categories – e.g. Danes, analysts, etc.
  • I thanked, and loved, and “awesome’d” and “great’ed” a lot.
  • Sharing – giving credit, not taking it. I always mentioned the source or the account where I had picked up a link.
  • Sharing the love – retweets were focused on positive news, positive sentiments and uplifting current events. I also checked the wording of the original tweet before RT’ing to avoid contamination of my positivity.
  • Getting personal – my personality and emotions were conveyed more by sharing private interests such as books, cats, travel and science fiction.
  • Language Disclaimer – all of the above choices were based on my non-native perception of the English language, and may have been different from Webster’s Dictionary which is the basic semantic interpreter used in lexical hypothesis.

What I didn’t do

Humour doesn’t travel well, so any jokes, irony, satire and cartoons were not part of echrexperiment. I may have gotten carried away occasionally, but consciously tried to avoid it.

Politics are a powerful emotional trigger, so I avoided RT’ing or engaging in conversations with political statements. That wasn’t the mission.

Automation is a powerful tool to increase the quantity of your social media posts, but with automation things like timing and engagement suffer. Sometimes, due to other news, automation may even lead to displaying insensitivity.

Automatic response is a convenient way to further promote your services and invite people to connect. But it just isn’t personal. Despite all these lovely people addressing me by name. I did not send messages to thank people for the follow, but I checked their profile and retweeted where I could to show my appreciation.

What Watson had to say about @echrexperiment

The app itself produces a lot of detail as you can see from above. Below I grouped the result into more familiar charts to share some highlights. To make sure I picked a really nice person as control, I chose President Obama’s Twitter @potus. But please remember – it’s probably mostly his staff tweeting. And they seem to have done an excellent job.

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Obama – it appears – is very agreeable on Twitter, and my experimental lovely/nicey/catsy account matches this impression very nicely. We are both very open, although I am lagging on conscientousness, but hey –  I am not the President.

Digging deeper into selected parameters, revealed some interesting characteristics related to being a President or just trying to be a nice person.

We can all agree that values should be an important parameter if you are President of the United States. Strangely enough Obama wasn’t all that keen on change, and more inclined to be conservative. For self enhancement … we have identified the villain – the one parameter that makes my original Twitter account so repugnant. I leave the graph to stand on its own.

Meanwhile, President Obama scored a resounding Zero on self-enhancement – but he made it to the top already.

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President Obama’s most distinguishing need is the need for structure. Love – it seems – he gets a plenty.

On the other hand, my original self seems to have enough structure in her life.

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But here’s the greatest insight from this entire exercise – other than confirming that it is possible to change who you are, or rather how you are perceived:

When it comes to curiosity, all you need to do is be a positive tweeter and include lots of cats.

 

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Rätt Data i Rätt Kontext

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Introduktion till nätverket Digital CMO

Av Peter Johansson

Digitaliseringen har gett marknadsföringen tillgång till mätbara data och drivit branschen ljusår framåt. Men det ligger en utmaning i tolkandet av dessa data. En utmaning som nya nätverket Digital CMO har tagit sig an.

Reklambranschen är en av de branscher som anammat digitaliseringen på mesta sätt. Idag har reklambranschen inte bara en uppsjö nya digitala kanaler att rulla ut sina budskap via, de kan även bygga sina kampanjer och mäta deras resultat med en precision som snuddar vid individnivå.

Det varma mottagandet av digitaliseringen kommer av naturliga skäl: Det datadrivna tankesättet är en grundstomme i marknadsföringen. Att använda kunddata som verktyg för att skapa relevanta budskap är vad jobbet går ut på, så att säga.

– Data som styrmedel för kommunikation är något som alltid legat naturligt för marknadsförare. Man har ju alltid jobbat med att ta fram sina målgrupper, definiera vem man ska prata med, i vilket sammanhang och sedan tajma det, säger Elisabeth Bitsch-Christensen, nätverksledare för Stockholmskretsens nystartade nätverk Digital CMO.

Inte bara data, data, data

Det gäller dock att inte stirra sig blind på siffrorna. Det finns otroligt många stand-alone verktyg som alla på sitt sätt utlovar Utopia. Men det räcker inte med data på ett pie-diagram som visar vad som har hänt. Det verkliga värdet av dina data kommer först när de tolkas utifrån ett relevant sammanhang. Som den amerikanska tidsskriften Forbes beskrev det när de nyligen vände på statistikern W. Edwards Deming klassiska citat ”without data, you are just another person with an opinion”

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”Without an opinion, you are just another person with Data”.

– Vad vi behöver är system som sätter detta i perspektiv, som ger bakgrund och kontext för den data som visas, och som lägger till aspekter som mänskligt beteende, makro- och mikroekonomiska faktorer och disruption. Vi behöver skapa insikt av data och applicera det till företagets utveckling och mål, säger Elisabeth Bitsch-Christensen.

Hur kan nätverket hjälpa till?

– Det finns otroligt många kloka människor i Stockholm och Sverige som har tagit till sig detta tankesätt från den ena eller andra vinklingen, och dessa människor behöver ett forum där det kan möta kolleger och stakeholders.

Därför har hon startat nätverket Digital CMO. En första träff hölls i september och ytterligare tre träffar är spikade under hösten. Närmast, den 7 november, fördjupar sig nätverket på affärsnyttan med beteendedata. Elisabeth Bitsch-Christensen har bjudit in Mikael Karlsson från Dagens Analys och Andreas Quensel, analyschef på Expressen.

– Vi kommer att bjuda in föreläsare, och själva berätta om våra erfarenheter. Vi tittar på trender och fördjupar oss i rapporter. Vi kommer att kommer att ha kul också, det är en viktig del av marknadsförarnas vardag, avslutar Elisabeth Bitsch-Christensen.

Make your Market Data Speak – and become a sales hero

Let’s all agree: Marketing is a strategic and mission critical function in any business. But unfortunately, this is rarely recognized. To prove your value as a marketer, show that your marketing investment supports the business.

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The ongoing discussion about ROI and metrics is sidelining the key issue: It’s no longer enough to measure number of leads generated in push-campaigns, you need to measure engagement and generate quality behavioral data. Marketing contributes to business strategy and growth. And you – the marketing professional – can become a hero for the sales organization by turning the data into valuable insights.

What we as modern marketers need to do is to focus on the business and how marketing can be even more successful through collecting the right data to work smarter and engage the right audience. For me, it’s always been about the data. And luckily for me – it’s available from just about everywhere. Marketers need to take the front seat in the digital era and learn why and how data driven decisions make a difference for marketing impact.

“Customers today expect—and demand—a seamless and relevant experience,” says Teradata. “They have grown accustomed to marketers’ knowledge of their preferences and anticipation of their needs. Fractured or conflicting messages from a brand make marketers seem unorganized and annoy customers, sometimes even driving them away.”

The topic of data and marketing is making it’s way into the board room, and decision makers require market and customer centric data to guide them.

Johanna Lindskog Lindell, a Swedish data strategist and PR professional, explains:

“Just like your company, your customers leave a digital trace. Customers expect you to know and understand their interests and preferences. With each interaction between you and your customers, they become more and more open and transparent exposing their behaviour and interests. Make use of these insights so that they can become the building blocks of your business.”

Easier said than done

In his blog in June, 2015 Jonathan Buckley of Qubole provides some useful insight on what it takes to create a datadriven culture in the enterprise, emphasising the need for both visionaries, tools and accountability in the process. But not all of us are sitting at the big round table, and for marketing to take a seat where visions turn into strategy, there is a both bottoms up and top down approach.

Johanna is a major influencer in the Swedish PR-world. In her regular blog on Resumé, published by Bonnier Business Media (in Swedish) she elaborates on how to build a datadriven strategy that keeps you out of trouble and gets you closer to the board room when decisions are made:

  1. Consolidate your data

Combine the data available in your organisation to drive strategic decisions, understand your customers and the perception of your brand. To strengthen your brand, you need to understand your position in the market…

  1. Listen

Success depends on how well you identify and understand your customers by letting their data speak to you. It’s not just about your brand and what you want to communicate. By listening you will understand what type of problems people want to solve, and what interests them. These insights are invaluable for your business.

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  1. Develop strategic campaigns

By listening you will gain insights and understand what drives your customers, what their engagement is about and how they perceive your brand. Using this data you can create strategic activities which can be applied to your entire organisation.

  1. Optimise and improve, try and try again!

Optimise your campaigns as you go by interpreting the information shared by your customers, and stay focused on customer driven marketing. Most companies and most people want to see metrics after a certain time period. I prefer comparing data with yesterday’s data. Mostly to see how well I have succeeded, what I can optimise and what I can improve.

What’s a petabyte?

So what is datadriven marketing? It is the creation of value that supports business objectives and your strategy. And it’s really quite mind boggling, how much data we as marketers have access to.

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In less than five years from today, experts predict that our annual data creation will reach nearly 45 trillion gigabytes, that’s 45 million petabytes. The human brain is estimated to store the equivalent of 2.5 petabytes of binary data. 2.5 versus 45 million petabytes.

You could also say that the available data in the world is more than what is stored in the brains of the entire population of – say – The Netherlands.

With all this data available to individuals, corporations, and governments, you will benefit hugely if you build your marketing strategy and execution on data.

When data is leveraged brilliantly, it can reveal highly useful patterns and trends. And you will find things to improve, not just in marketing but in other business functions as well.

 

 

 

 

Success is about balancing data, art and poetry

Some people – including many marketers – think data is dull and boring. I don’t. Data has poetry when you know how to look. To let it speak to you is  pure art; it will help you develop a successful datadriven strategy.

Nonsense

 

For a while now I have been struggling with definitions and perspectives on the enigma of datadriven marketing. There are so many different skills involved – and so many departmental functions that hold a stake. To understand the confusion, you might like to read my previous post What is Datadriven Marketing Even the dictionaries, let alone the stakeholdes themselves, are struggling with the term. From a marketing perspective, however, there is a clear purpose:

Datadriven marketing means capturing and analyzing data from the abundance of available transactions and interactions between you, your company and your market – and turning them into meaningful conversations that engage your audience.

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Click here for more of these excellent cartoons.

 

Datadriven marketing is pretty straightforward

“This is what works: being clear about a Call to Action, knowing your audience, crafting content that’s got a story to it, measuring and analysing results and adjusting based on the data.” (Jim Rosenberg, Chief Communications Officer at Accion)

There are some key words in this statement which have evolved into separate – and rather hyped – marketing disciplines:

  • Know your audience – the hype word here is personalisation
  • Content with storytelling – the hype word is Content is King
  • Measuring and analysing results – the hype word is Business Intelligence

What perplexes me is that each of these components seem to be addressed separately depending on what is the hottest trend on the various expert forums and conferences aimed at marketers. Add the #InternetOfThings to the mix and it gets even more disassociated from the real business purpose of marketing.

Getting personal

What if marketers listened to their data before they applied it to a mailing list with names, company size and job title? Personal contact information provided over completed online forms tends to be incorrect, flimsy and incomplete. Often it is  contaminated in the mailing application by duplicates and record matching, and the risk of antagonizing the recipient is real.

Personalisation should not be about getting the name and job title right, it should be about getting personal to the extent that the timing, the message and the format is relevant to the person receiving the communication.

Get aligned – or perish

What if marketers worked their way backwards from the business objectives to the content that was needed and embraced by the sales organisation to achieve them?

Studies show that despite “Content is King”, many sales teams do not fully utilize these carefully drafted assets:

Only 9 percent of content created in enterprise marketing departments is viewed more than five times by the sales department, according to Docurated’s latest State of Sales Enablement report.

Apart from an apparent lack of strategy around content creation, marketing and sales teams are not communicating and appear to be creating content in silos. Read more here.

How to turn metrics and analyses into actionable insights

The good news is that organizations are collecting and creating more data, but they also have better analytics tools and techniques available. The bad news is that there can be too much of a good thing. Paul Blasé from PriceWaterhouseCoopers explains it like this:

“For example, they (…the senior management…) can debate, ‘well why did the market grow at this rate when I assumed [it would grow] at this rate; or why did this competitor gain share versus me, when I assumed the opposite would happen because I dropped my price? It’s about combining the intuition and the experience with the science of data analytics together to help an executive team make better decisions, and that’s where we’re seeing traction.”

The challenge is to allow the poetry to enter the discussion – expressed by Blasé as combining intuition with experience. Because what characterises these questions is that executives tend to address historical data with lagging indicators and based on KPIs and other metrics they defined not from insights they need, but from data that is available to them within the scope of the reporting and analytics tools that they currently use.

The Harvard Business Review conducted an interesting study among graduates who were in positions where the focus was on researching competitive intelligence. And concluded that only half of the companies actually use the competitive intelligence that they collect.

Why? Because when decisions are made, he or she who shouts the loudest, normally defines the game. So if data is collected and interpreted only to reconfirm an assumption or justify a strategy already defined, or if the actual data provides insights that are countering the loudest shouter, management may end up making some very bad decisions. But you can turn it around – if you listen and understand what the data tells you, successful decisions will help your business and your career. One of the examples from the Harvard Business Review study is from a pharmaceutical company that used the data to make business related decisions:

A common theme across industries was the smart reallocation of resources. One analyst told us that their company had stopped development on a project that was consuming lots of local resources after the analysis indicated it wouldn’t be effective. They then re-applied those resources to an area with true growth potential — that area is now starting to take off. In a different company, an analysis led to the cancellation of an extremely high-risk R&D program. (Benjamin Gilad, Leonard M. Fuld, Harvard Business Review Jan 28, 2016)

Read more about why organizations struggle to get data cultures right in this article by David Weldon from Information Management.

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From chaos to order

In the second half of this video  the SBI (Sales Benchmark Index) Revenue Growth Maturity Model defines the evolutionary flow from data strategy chaos to order:

  1. Chaos – the organisation has a corporate data strategy but it is not translated into a functional direction.
  2. Defined – there is both a corporate and functional strategy, but they are not implemented.
  3. Implemented – now, the strategies for both corporate and functions are implemented but remain separate entities and not aligned.
  4. Managed – now we have aligned the strategies to run the organisation with a defined goal and actionable insights
  5. Predictable – aligned both internally within the organisation and including and integrating external data sources from the market.

According to SBI, 51% of US companies are still at level 1 – in a chaotic environment where strategy is neither communicated nor aligned with the business.

That is the pitfall that digital marketers must avoid – the disalignment of business objectives and marketing strategy.

 

 

 

 

 

 

 

How to win presidential elections with a digital strategy

“If the Democratic party were a body, Bernie Sanders would be the heart and Hillary Clinton the brain”

No one expects the Spanish Inquisition – and initially, nobody expected Barack Obama to have a real chance – even more so to get re-elected for a second term. What was his secret? It was being both the brains and the heart.

His method was using data to gain insight into what people care about and address that issue at each and every rally right there and then. When the issue was burning the most.

For us non-US observers it is worth remembering that the key to winning the candidacy as well as the election is not necessarily winning the votes of those who walk to the ballots. It’s about engaging those who wouldn’t.

A datadriven digital strategy

A datadriven strategy enables you to identify the issues that engage your audience.

For his first term election campaign, Obama succeeded in engaging a generation – the generation of social media which was just about to take off at the time.

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He was the first major political candidate to understand the power of sentiments and the power of the voice of the people outside the established channels such as television and news anchors.

By 2012 for the re-election he – or his team of advisors – had understood the power of using data to refine the message and making it timely.

The power of the crowd

As I am writing this article, the final numbers for Iowa have not yet come in, but it is a 50-50 race between Bernie Sanders and Hillary Clinton. In social media, Bernie Sanders has won (according to this Reuters analysis.)

U.S. Democratic presidential candidate Bernie Sanders raises a fist as he speaks at his caucus night rally Des Moines

Bernie Sanders raises a fist as he speaks at his caucus night rally Des Moines. REUTERS/Rick Wilking

Sanders was mentioned 77,000 times versus Clinton’s 55,000 times (Brandwatch) and gained 15,699 new Facebook followers on the one day. Clinton’s Facebook page only came third with 6,210 new followers that day, trailing Donald Trump’s 10,704.

As in all data, one must not jump to easy conclusions and take the number at it’s face value. There can be many different reasons why someone chooses to like a Facebook page – you could be liking an opponent to observe and learn, or to troll and create a disturbance. The second level of such an analysis should therefore always be a sentiment analysis and catalogueing the social media influence of these new followers to be able to conclude credibly whether this will impact a future election result.

 

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But one thing is certain – you could easily turn the intelligence gathered from this analysis into a practical campaign such as Obama did. One example is given below where the objective was to engage would-be supporters who just had not registered to vote with BigData combined with TV advertisement.

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I can’t wait to read more analyses on how the candidates fare by making their data speak. May the best data whisperer win.

 

More interesting links to the impact of social media on US elections:

 

 

 

Marketing Tips and Tricks

The three touch engagement strategy for audience acquisitions at business events: Idea – Engagement – Push

Source: Where is everybody – where’s my ROI? Tips and Tricks to attract the right audience at your event

Where is everybody – where’s my ROI? Tips and Tricks to attract the right audience at your event

If you read my previous blog entry, you may still be looking for the best way to find the golden audience that makes you best friends with the sales teams. Here are some suggestions I have collected over the years:

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Plan with the end in mind

  • Don’t just set a date, build a 3-touch-strategy together with your stakeholders (the sales teams in most cases).
  • The theme and message has to promote and strengthen the conversations that your sales teams are having with their target prospects. Don’t push some new message or vision down their throats if this is not what their targets are interested in.
  • Be flexible – if the conversation has moved over the 8-10 weeks of planning before the event, make sure to have alternatives ready to add to the speaker list.

Email marketing – and other channels

  • Don’t publish it all at once, when you start the invite process – build an engagement staircase with at least 3 touches.
  • Expand your email campaign with social media engagement through dedicated, branded Linkedin groups, with a short, recognizable and easy to remember hashtag to use across channels before, during and after the event.
  • Another great tip is to prepare your tweets and posts so that your colleagues across the company can share without sounding like a marketing machine.
  • Make it personal, local, fun – whatever their preference is.

For your email campaign – here are the three touches I would recommend:

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Launch the idea of an event and pre-announce the date. Get the theme out there to gauge interest from your target audience. If you have a star speaker name, don’t let the cat out of the sack just yet. Have a call-to-action button for “sign me up” or “tell me more” – and make sure there is a response on the second one.

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First real invite – allowing people to sign up based on an agenda with topics and speakers that are “glocal” – have a global vision but either are local or have local recognition. Always have a button “sign me up” and “tell me more” to encourage a dialogue.

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Now let the cat out of the sack. Make a big boom invite only promoting date, theme, agenda and your star.

Less is more – let people click through if they want to deep dive into agenda or speaker profiles etc. That way you can capture who is interested so that your sales teams can follow up with personal emails or telephone calls.

Still not there? Time to call the cavallery

And if all fails – if you have not met your quality registration target – go the extra mile – engage with your sales teams, show them the gap between their expectation on the attending audience and their sales target accounts.

Give them a cheat sheet with talking points about the event.  Remember, you know everything about how great it will be – but they probably don’t event know the speakers or content in detail yet. Get them excited, build a dashboard or some other gamification element to let them compete with each other (and make sure there is a decent prize for the winner, so get that on the budget from the very beginning).

Help them help you succeed.