Painting a Masterpiece With Social Data

The Subconscious Art of Social Media Intelligence

Great art is more than great technique. Great art shares a unique perspective of human existence or philosophy.

We don’t always understand artistic interpretation. But when we do, we marvel at its beauty and it makes us feel like we’re part of something larger.

Social intelligence has a lot in common with art.

In a world where customer centricity is everyone’s goal, social intelligence can offer a glimpse into society from a new perspective. A new perspective that can give you invaluable insights into how to connect with their hearts and minds.

But getting human insights from social data is a messy process.

Unsurprisingly, there is an incredible amount of data. New technologies can help non-technical people gather and sort through the data, but social data itself is not an insight – it’s an input.

Like artistic vision, insights sit in the subconscious space of the mind. They are a wonderful balance between data, context and intuition – and they are fundamentally human.

Finding Your Muse

Finding Your Muse

Like with every new innovation, hype can often overtake reality. Many organisations are still trying to figure out what value social data can give them. So, we surveyed over 200 social data professionals across the world to explore their current social data analysis practices, structures, their challenges and use of technology in The State of Social Intelligence 2019.

We’ve used the findings to demonstrate four essential elements where you should focus your efforts to get more measurable brand value from social data.

The goal? For you to find inspiration and master the art of social intelligence.

4 Essential Elements
The human minds that power social intelligence, giving context, meaning and action to the data
The tension between how knowledge is generated in practice versus how it is implemented through process.
The iterative questioning of the data in different ways to answer the objectives and purpose, and give value to the data.
The selection and adoption of the right combination of technology according to needs and specific applications.

Social Intelligence is a movement misunderstood

Social media and digital technologies have revolutionised human communication. This public digital discourse offers unrivalled insight into modern behaviour. The power to quantify digital behaviour and discover the hidden meaning in mass online conversations is made possible with social intelligence.

But like many new movements, it has been considered avant-garde. By its nature, social intelligence requires an unconventional way of working.

And when something is new, it doesn’t always produce the right results quickly. But little wins can bring great momentum. Learning from the successes (and struggles) of the brands around you can help move social intelligence from being perceived as unconventional to democratised across your organisation.











If your journey into social intelligence has been bumpy, you’re not alone.

52% say that senior leaders do not clearly understand their objectives or outputs.

“We have a real ‘Lost in Translation’ problem at the moment with social data. The potential is there to help senior stakeholders make better decisions, but this is too often frustrated by a failure to deliver clear insight”

Jeremy Hollow

Founder & MD, Listen + Learn Research

A Lack of Understanding

Social data analysis has been a focus of activity for many business units and disciplines. And has even created a new type of organisation – those solely specialising in the analysis of social data.

But across all areas of work, the lack of leadership understanding affected the perception and use of social data across the organisation.

Click below to find out which professions took part in our survey

30%
8%
21%
11%
30%

Take part in our ongoing survey

Which discipline best describes your role?

31%

of organisations have no social data democratisation


21%

of respondents struggle to get leadership buy-in


52%

of respondents have no knowledge of how social data is used across their organisation

When you’re creating something new, it is important to know that your efforts will be worth it

80%

of respondents agree that social data provides unique insights that cannot be obtained from other data or research sources.

Percentage of respondents who feel social intelligence has met or exceeded their expectations

Overall
Client Side
Social Intel.
Research
Marketing
PR
Other

Take part in our ongoing survey

has social intelligence met or exceeded your expectations?

No One Size Fits All

Over half of all respondents surveyed reported successful social intelligence initiatives. Sixty-five percent ranked creating actionable insights and tracking the right metrics as elements very important to meeting expectations.

Interestingly, these are two elements where there is no one size fits all approach – suggesting that flexibility and subjectivity are essential for success.

“As advanced as technology has gotten you still need analysts who understand the business, technology and social conversations to deliver successful social intelligence”

Jackie Cuyvers

Founder and CEO, Convosphere

  Creating actions from insights Tracking the right metrics Producing deliverables quickly Integrating with other data sources Maintaining best practice
18 13 9 9 9
  Tracking the wrong metrics Not creating actions from insights Not Proving ROI Not getting more buy in Choosing The wrong tools
18 15 10 10 9

Transforming your approach

Despite a lack of c-suite understanding, and the challenges faced to uncover fundamental truth and create action from social data, the survey shows that the social intelligence movement is gaining momentum.

Every organisation is at a different place on their social intelligence transformation – with varying levels of sophistication (and success). The one thing that successful organisations have in common? They discovered that listening is not enough. They know that, to take action, social intelligence requires a blend of data, business and social science.

This is a transformation journey, it needs a team and organisational buy-in.

You may have already sketched out your vision and started to apply the paint, or you may just be starting to imagine what is possible and be finding your focus. Either way, your social intelligence transformation won’t get very far without a plan.

Using the data from The State of Social Intelligence Survey, we highlight four elements critical to transforming social data into measurable business results.

The four elements critical to transforming social data into measurable business results

  • 1

    People

    the human minds that power social intelligence, giving context, meaning and action to the data.

  • 2

    Structure

    the tension between how knowledge is generated in practice versus how it is implemented through process.

  • 3

    Process

    the iterative questioning of the data in different ways to answer the objectives and purpose, and give value to the data.

  • 4

    Technology

    the selection and adoption of the right combination of technology according to needs and specific applications.

  • People

    Social data is an abstraction of real-life, and real-life can be complicated. Social data analysis technologies can help to gather, sort and process online content and conversations. But we need context to understand the real meaning.

    Without human interpretation, social data is just a bunch of jumbled conversations. Human interpretation illuminates a deeper understanding of the “why” behind online interactions – providing the context. Your people should be at the heart of your social intelligence initiatives. Without them, you only have data.

    The social intelligence industry has grown from listening to brand mentions and measuring content performance to asking questions and testing hypotheses to understand human behaviour. Improved social data analysis technologies have helped to facilitate this change.

    But much of the industry maturity has been driven by people and their imaginative use of the data. Early enthusiasts have been pioneering social intelligence practices for over a decade.

    The number of years respondents have worked in social intelligence

      Less than 1 year 1-2 years 3-4 years 5-6 years 7-8 years 9-10 years More than 10 years
    3 9 24 19 10 17 18

    Today, many now consider social data analysis as their primary responsibility in their job role.

  • 66%

    of respondents consider social intelligence their primary job responsibility

  • 34%

    of respondents consider social intelligence as part of their job responsibilities

  • The percentage of people who have advanced and expert skills in

    Defining a new project
    Choosing the most effective method/metrics
    Analysing and Interrogating the data
    Generating actionable insights

    The key to making use of social data insights is knowing how to interpret them. In a data-driven world, human interpretation is as important as ever. The social intelligence process requires deep cognitive and subjective skills to uncover new meaning from the data. But only 33% feel they have the space and support in their roles to achieve this.

    This year, fighting to attend client meetings, an inability to access specialised training and support, and the shortage of other skilled practitioners to speak with, contribute to feelings of isolation and a lack of support. In the next twelve months, 45% of organisations plan on investing in more people but without the right support, that investment could be wasted.

    Will machine learning and artificial intelligence help? 84% of those surveyed think so. But AI will empower rather than replace social intelligence practitioners.

    Areas where artificial intelligence will affect social intelligence practices

  • 24%

    Improve Data Gathering

  • 40%

    Improve Data Analysis

  • 20%

    More Freedom to Interpret data

  • 7%

    No Impact on Work

  • 9%

    Unsure about the future

  • Structure

    Everyone has become really good at collecting social data. But the real challenge is putting that social data into context and making sense out of it. Part of what’s missing is knowing what everyday business situations it can be applied, and if it has more than one purpose.

    Many business silos have an interest in the value of social data. Even non-technical people can access solutions to gather, sort, and make sense of the connections and relationships in the data. But their business objectives and KPIs are heavily influenced by the business silo in which they operate.

    This year, we saw a real disparity in how social intelligence is structured in the organisation. At times, they were part of marketing, others PR, analytics, and others research. Interestingly, over half of respondents did not know or were unsure about who else was using social data in their organisation.

    Percentage of respondents who know if other business silos are using social data

  • 52%

    Don't Know

  • 42%

    Know

  • 6%

    Unsure

  • Nine percent of organisations running successful social intelligence programmes cited creating and maintaining best practice as an element essential for success. The siloed nature of current practices does not allow this to happen effectively. When asked about how social intelligence activity is structured in the organisation, over a quarter of companies are still pursuing uncoordinated pockets of activity.

    How social intelligence activities are structured in the organisation

  • 31%

    Uncoordinated Pockets of Activity

  • 18%

    Localised shared activity

  • 29%

    Centralised group with some coordination over activity

  • 22%

    Centralised group closely coordinating activity across the organiatin

  • 28%

    Uncoordinated Pockets of Activity

  • 33%

    Localised shared activity

  • 28%

    Centralised group with some coordination over activity

  • 11%

    Centralised group closely coordinating activity across the organiatin

  • 0%

    Uncoordinated Pockets of Activity

  • 18%

    Localised shared activity

  • 18%

    Centralised group with some coordination over activity

  • 64%

    Centralised group closely coordinating activity across the organiatin

  • 39%

    Uncoordinated Pockets of Activity

  • 0%

    Localised shared activity

  • 39%

    Centralised group with some coordination over activity

  • 22%

    Centralised group closely coordinating activity across the organiatin

  • 43%

    Uncoordinated Pockets of Activity

  • 13%

    Localised shared activity

  • 33%

    Centralised group with some coordination over activity

  • 10%

    Centralised group closely coordinating activity across the organiatin

  • 22%

    Uncoordinated Pockets of Activity

  • 33%

    Localised shared activity

  • 33%

    Centralised group with some coordination over activity

  • 11%

    Centralised group closely coordinating activity across the organiatin

  • 31%

    Uncoordinated Pockets of Activity

  • 18%

    Localised shared activity

  • 18%

    Centralised group with some coordination over activity

  • 31%

    Centralised group closely coordinating activity across the organiatin

  • “The results tell us two things. First, marketing is still the driving force behind social intelligence. The second, coordination efforts are still not yet valued as an opportunity to use social intelligence to make impact across an organisation – from marketing to sales to customer experience”

    Marianne Hynd

    Director of Operations, Social Media Research Association

    Decision Making

    As you plan for transformation, keep in mind that social intelligence can be used in multiple areas of business decision-making. A huge part of your transformation journey is finding the most valuable use cases for your organisation. This is an iterative process that takes time, patience and a willingness to learn. Here are the common areas where social intelligence is being used in business-decision making this year.

    Top 5 use cases for social media intelligence (by industry)

  • 1
    81%

    Social Media

  • 2
    77%

    Market Research

  • 3
    73%

    Brand

  • 4
    69%

    Competitive Intelligence

  • 5
    64%

    Marketing Analytics

  • 1
    94%

    Social Media

  • 2
    78%

    Brand

  • 3
    78%

    Marketing analytics

  • 4
    72%

    Market Research

  • 5
    72%

    Public Relations

  • 1
    82%

    Social Media

  • 2
    72%

    Brand

  • 3
    72%

    Positioning

  • 4
    72%

    Market Research

  • 5
    64%

    Product Development

  • 1
    100%

    Market Research

  • 2
    67%

    Competitive

  • 3
    61%

    Brand

  • 4
    56%

    Innovation

  • 5
    56%

    Social Media

  • 1
    90%

    Social Media

  • 2
    80%

    Advertising

  • 3
    77%

    Brand

  • 4
    73%

    Competitive Intelligence

  • 5
    70%

    Marketing Analytics

  • 1
    100%

    Public Relations

  • 2
    78%

    Brand

  • 3
    78%

    Social Media

  • 4
    75%

    Market Research

  • 5
    67%

    Marketing Analytics

  • 1
    81%

    Social Media

  • 2
    75%

    Market Research

  • 3
    75%

    Brand

  • 4
    69%

    Competitive Intelligence

  • 5
    62%

    Advertising

  • Take part in our ongoing survey

    What is your primary objective for analysing social data?

    Process

    Many people across the organisation are being empowered to make use of social data to inform their work and inspire their thinking. They have access to unprecedented amounts of data. But extracting and refining quality actionable insight from constantly flowing conversations isn’t easy.

    Overworked minds are not looking to process data that doesn’t instantly make sense. People want immediately usable insights with tightly written summaries of interesting findings. And they want to know how to use them.

    The trouble is, social data analysis is hard. Social data insights don’t all have the same process through which they are developed. They have their own objective, purpose and value – they are not created equal.

    Without process, people do not know what to do.

    Using data from the State of Social Intelligence survey, we found four areas to consider when refining your processes: analysis objectives, analysis focus, analysis methods and context holes.

    Analysis Objectives

    There’s more than one use for social data. Too often social data analysis starts without a clear idea of what is being tested or how the insight is going to be used. It’s impossible to meet organisational expectations without first knowing the objective. But it can be difficult to know how to ask the right questions. Seeing how other organisations are using social data can help to refine your objectives. Here’s how other organisations are using social intelligence in business decision-making.

    Favourite social intelligence objectives

  • 1
    72%

    Customer Insights

  • 2
    66%

    Measuring Campaigns

  • 3
    57%

    Understanding Behaviour

  • 4
    56%

    Understanding Sentiment

  • 5
    54%

    Brand Positioning

  • 1
    72%

    Measuring campaigns

  • 2
    50%

    Identifying opportunity

  • 3
    50%

    Reaching new customers

  • 4
    50%

    Segmentation

  • 5
    50%

    Customer insight

  • 1
    90%

    Customer insight

  • 2
    64%

    Customer acquisition

  • 3
    64%

    Identify opportunities

  • 4
    64%

    Understanding sentiment

  • 5
    64%

    Messaging

  • 1
    72%

    Understanding sentiment

  • 2
    72%

    Customer insight

  • 3
    67%

    Understanding behaviour

  • 4
    61%

    Customer profiling

  • 5
    61%

    Competitive advantage

  • 1
    80%

    Customer insight

  • 2
    83%

    Measuring campaigns

  • 3
    67%

    Brand positioning

  • 4
    67%

    Managing reputation

  • 5
    63%

    Competitive advantage

  • 1
    78%

    Campaign strategy

  • 2
    78%

    Measuring campaigns

  • 3
    67%

    Customer insight

  • 4
    56%

    Understanding sentiment

  • 5
    55%

    Managing reputation

  • 1
    75%

    Customer insight

  • 2
    69%

    Understanding behaviour

  • 3
    62%

    Understanding sentiment

  • 4
    56%

    Customer profiling

  • 5
    50%

    Segmentation

  • Focus

    Although you might know the objective of your analysis, there is still an impossible amount of social data available. Not all of that data will be valuable to you. The objective of your analysis affects the focus of your data gathering strategy – is it brand mentions you’re looking for? The influential people who are discussing a topic? Or maybe you’re looking to understand purchase intent or unmet needs? It’s important to write clear search queries to gather most relevant data. Here’s where other organisations are focusing their social intelligence activities.

    Most common areas to focus social data analysis

  • 1
    52%

    Topic analysis

  • 2
    51%

    Audience analysis

  • 3
    43%

    Brand analysis

  • 4
    37%

    Competitor analysis

  • 5
    36%

    Consumer behaviour

  • 1
    50%

    Audience analysis

  • 2
    44%

    Brand analysis

  • 3
    39%

    Topic analysis

  • 4
    33%

    Industry trends

  • 5
    33%

    Influencer analysis

  • 1
    64%

    Topic analysis

  • 2
    54%

    Audience analysis

  • 3
    45%

    Brand analysis

  • 4
    36%

    Consumer behaviour

  • 5
    27%

    Influencer analysis

  • 1
    67%

    Topic analysis

  • 2
    44%

    Consumer behaviour

  • 3
    44%

    Competitor analysis

  • 4
    39%

    Brand analysis

  • 5
    33%

    Influencer analysis

  • 1
    67%

    Audience analysis

  • 2
    50%

    Competitor analysis

  • 3
    50%

    Brand analysis

  • 4
    40%

    Topic analysis

  • 5
    27%

    Consumer behaviour

  • 1
    79%

    Topic analysis

  • 2
    44%

    Consumer behaviour

  • 3
    44%

    Brand analysis

  • 4
    33%

    Influencer analysis

  • 5
    33%

    Audience analysis

  • 1
    62%

    Audience analysis

  • 2
    50%

    Consumer behaviour

  • 3
    50%

    Topic analysis

  • 4
    37%

    Competitor analysis

  • 5
    25%

    Influencer analysis

  • Methods

    The purpose of social intelligence is to create human-centric insights, there isn’t one right way to achieve this. Social data analysis is about iterative questioning of the data in different ways to answer your question. The insights hidden in social data have to be coaxed out through different analysis methods. Here are the most commonly used.

    Most common methods of social data analysis

  • 1
    78%

    General analytics

  • 2
    72%

    Share of voice

  • 3
    71%

    Trend analysis

  • 4
    70%

    Topic analysis

  • 5
    64%

    Demographic analysis

  • 1
    83%

    General analytics

  • 2
    67%

    Demographic analysis

  • 3
    67%

    Trend analysis

  • 4
    61%

    Content performance

  • 5
    60%

    Topic analysis

  • 1
    100%

    Trend analysis

  • 2
    91%

    Topic analysis

  • 3
    82%

    Share of voice

  • 4
    82%

    Thematic analysis

  • 5
    73%

    Visual analysis

  • 1
    78%

    Topic analysis

  • 2
    78%

    Share of voice

  • 3
    78%

    General analytics

  • 4
    61%

    Emotional analytics

  • 5
    61%

    Trend aanalysis

  • 1
    83%

    General analytics

  • 2
    73%

    Content performance

  • 3
    73%

    Trend analysis

  • 4
    71%

    Share of voice

  • 5
    68%

    Reputation analysis

  • 1
    90%

    Trend analysis

  • 2
    78%

    Sentiment

  • 3
    78%

    Topic analysis

  • 4
    78%

    Share of voice

  • 5
    78%

    Content performance

  • 1
    75%

    General analytics

  • 2
    75%

    Sentiment analysis

  • 3
    75%

    Share of voice

  • 4
    69%

    Demographic analysis

  • 5
    69%

    Visual analysis

  • “Part of the learning challenge teams face is that they need a deep understanding of how social intelligence fits into their broader set of tools and methodologies they can use to answer a business question. If they don’t understand a method, then it is less likely to be chosen as a method by the executing teams”

    Kevin Hains

    Insight Manager, Waitrose and Partners

    Filling in the holes

    Social data, when leveraged correctly, can bring a brand closer to the consumer, and offer a genuine glimpse into modern behaviour.  There is no substitute for hearing about experiences first hand. But social data doesn’t always have all the answers. The data gathered is often unstructured and biased – there is a risk of it being taken out of context.  To increase the social context of and connections between data points, organisations are turning to other research and data sources, here are the most common…

  • 67%

    Web analytics

  • 64%

    Search data

  • 60%

    Quantitative market research

  • 57%

    Qualitative market research

  • 25%

    Sales data

  • Technology

    Of course, none of this would be possible without technology. Humans need help to gather, sort and make sense of large volumes of jumbled conversations. Social data analysis technologies are at a constant pace of growth and evolution – continually giving organisations new ways to look at and make sense of the data.

    Technology is an enabler when it is embraced correctly.

    All organisations surveyed placed a high priority on investing in the right social data analysis technology. But, only 25% are confident that social data analysis technology will continue to meet their business needs. Unsurprisingly, technology stacking is a common trend to increase an organisation’s confidence to meet social intelligence objectives.

  • 3

    The average number of tools purchased by organisations

  • 85%

    of organisations invested in more than one social data analysis solution

  • 91%

    of respondents spent their budgets in social listening and monitoring technologies

  • The average annual cost of social data analysis technologies

  • 16%

    0-£10k

  • 22%

    £10-25k

  • 17%

    £25-50K

  • 17%

    £50-100k

  • 10%

    Over £100k

  • While 89% feel that they have the necessary skill and confidence to use these technologies, many professionals have to regularly analyse data manually because their analysis techniques are not supported.

    Percentage of respondents who reported to manually analysing social data

    Despite low vendor confidence and a need to manually analyse social data, there is a high optimism that social data analysis capabilities will grow in importance for organisational decision-making in the future.

  • 65%

    of respondents have a high confidence that social data analysis capabilities will grow in importance

  • Technology will always provide new mediums for realising your vision when you have the right people to power them. Social intelligence is at a constant pace of growth and evolution, technologies are continually being developed to help support that vision.

    How businesses plan on investing in social data analysis technologies over the next 12 months.

  • 51%

    will expand use of social data analysis technologies

  • 6%

    Plan on changing vendors

  • 3%

    will build proprietary solutions

  • 17%

    plan to reduce use of social data analysis technologies

  • Take part in our ongoing survey

    How many social data analysis technologies do you currently have a license for?

    Support your team

    Social intelligence begins and ends with people. To support your team, help others understand what you do, and to get more buy-in consider:

  • 1

    Promoting cross-organisational groups that work together, share ideas and create best practice.

  • 2

    Working to find the everyday business issues where social data can help and know what insights people need to fix them.

  • 3

    Selecting the right combination of technology according to your specific needs and applications.

  • 4

    Being pragmatic in your approach - change how you work depending on the problem you are trying to solve and create best practice around it

  • 5

    Getting the right insights to the right people, quickly.

  • 6

    Spoonfeeding insights - give them tightly written summaries, fundamental truths and let them know how they can use them.

  • 7

    Being prepared to continually refine your approach to keep up to date with industry changes.

  • 8

    Hiring a partner to guide, coach and empower your social intelligence team.

  • Take part in our ongoing survey

    Do you have any comments about your perception of the social intelligence industry or your ability to generate actionable insights from social data?

    Painting a Social Intelligence Masterpiece

    Everyone has become really good at collecting social data. Some organisations are also getting really good at knowing what to do with it. Others struggle to make sense of its volume and context, and convince the higher-ups of its value.

    One thing is for certain, social intelligence requires a long term commitment, people to make it work and wider buy-in to succeed. It is best approached pragmatically, by focussing on the individual requirements of each project as opposed to strict standardised processes. Rather than it being about the brand, it is about being immersed in the world of the customer and becoming part of it.

    Social intelligence should be treated as part of the customer experience and blended with other data sources to find the fundamental truth that is motivating people’s behaviour. One fundamental truth can inspire a new way to design experiences and create powerful messages that last.

    It is not only technology but people that are needed to connect the dots between what customers think, feel, say and do. Rational minds are needed to find the subconscious links between unrelated concepts and new ideas. When human insight is used to make business decisions, it becomes the core driver of compelling customer experiences. To make that commitment to yourself and your people is to paint your own social intelligence masterpiece.

    How we can help

    The Social Intelligence Lab is committed to helping you get more measurable brand value from social data.

    If you’d like to dig deeper into the results of our State of Social Intelligence Survey, you can download our free report here. In there you will find insights on current challenges, where budget will be spent in the next 12 months and how professionals are really using social data to identify and measure influencers.

    Or if want to dig even deeper into the tools people are using and their opinions on them, you can request access to our full report. We’ll also give you access to all the questions asked and the raw anonymised ata.

    Request Full Report

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