Social Intelligence: an Evolving Landscape

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SDL Proprietary and Confidential Social Intelligence, an evolving landscape Research evaluating the maturity of social media monitoring, social intelligence and the opportunities of the social data set.

Transcript of Social Intelligence: an Evolving Landscape

SDL Proprietary and Confidential

Social Intelligence, an evolving landscapeResearch evaluating the maturity of social media monitoring, social intelligence and the opportunities of the social data set.

SDL Social Intelligence commissioned a survey of those amenable to social data solutions and those with a business need for a data solution or BI tool, there were great findings we thought we should share.

Respondents were those with influence in the decision-making process and had budget to purchase at least one kind of data analysis tool.

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56%

What is the awareness of brands that relate to social intelligence?

56% of respondents were unable to identify a Social Intelligence brand.

Even when presented a list of 13 self-declared Social Intelligence brands, less than half could identify the brand name as a vendor of Social Intelligence products, services and solutions.

In unaided recall, Adobe Social, Radian6, SDL SM2 and Crimson Hexagon were named.

As it’s currently defined, “Social Intelligence” is a very misunderstood label.

Without prompting, Facebook, social networks, and various Google properties dominated the association with ‘Social Intelligence’.

Amongst a landscape of tool confusion, weak brand awareness and low conversion rates from the assessment phase to purchase, what does vendor success look like?

“The pricing structure and historical data available are more comprehensive”

“Good B2B understanding; existing relationship and ability to cater to our unique needs.”

“Provides real-time information on which to base decisions affecting expenditure of resources”

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51%

42%

51% see the opportunity in taking advantage of social data when it is clearly defined.

When undefined, a high recall of social data being “interesting but confusing” and “nothing but ‘tweets’ on Twitter and ‘likes’ and ‘status updates’ on Facebook”

42% agreed it to be an interesting and powerful data source.

The case for social data strengthens when presented with a compelling definition.

• Let’s define ‘Social data’ as:

“any user or participant-generated content published on the web. It is typified by the voluntary engagement between consumers, or with brands they engage with through activity in blogs, forums, video and photo-sharing sites, social-networking and microsites.  Analysis of this data is typically done with software that aggregates the data based on desired areas of interest.”

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13%We saw a 13% uplift in respondents choosing the “…is critical for business intelligence and decision-making” options when we presented our definition of social data.

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What is ‘social data’ currently used for?

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Perceptions: Benefits and BarriersThe top 3 benefits:

1. Candid feedback

2. Targeted

3. Inexpensive

– With honourable mentions for: access to historical data, highly predictive and access to competitor activity

The top 3 barriers:

1. Concerns about representative data

2. Privacy and compliance

3. Confusion about solutions available

– With responses also conveying lack of in-house resources to ‘digest’, ROI concerns and budget limitations

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72%

13%

Time: 72% - The biggest single problem customers face in their current role related to any data, analysis, visualization, or tools is bandwidth and skill-gaps

Action: 67% - The #1 use for ‘social data’ is customer engagement, not a platform for data mining and analytics that inform business KPIs

Complexity: 13% - without a clear definition or understanding of what ‘social data’ involves, “social data is interesting, but confusing”

67%

Thematic barriers to Social Intelligence

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• Our survey shows that the vendors which succeed at converting awareness to purchase of a social data solution make ROI clear and achievable in their messaging but ROI does not register in the top ten benefits of using social data, it is seen more as a barrier.

• Could this be further evidence of a poor understanding of how to best utilise the outputs of a monitoring tool? Are lots of numbers and charts getting in the way of the substance of data?

The ROI issue – a disconnect?

A social data solution has some essential business requirements that any vendor must provide.

1. Quality of data

2. Analytics capabilities

3. Agreeable total cost

4. High level of quality in customer support and client services.

Get the essentials in place and the following become critical issues when selecting a monitoring software solution.

+ UI

+ Customisation

+ Historical data access

+ International coverage

For those with “less input” in the decision-making process:

..the quality of customer support / service becomes a more important driver of preference.

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What pays for social data?

When it comes to budgeting for a business analytics tool…

..social data solutions are not displacing other solutions.

..funding for social intelligence projects or long-term software investment comes from trimming budgets elsewhere for 48%

..44% may need new budget to add a social intelligence solution.

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The biggest SINGLE problem customers face in their current role related to ANY data, analysis, visualization, or tools is bandwidth and skill-gaps

Data visualization

Privacy concerns

Compatibility / Interoperability of systems

Tight budgets

Data concerns

Unclear value / ROI / Justification

Time / skill constraints

3%

5%

5%

17%

25%

28%

72%

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The Social Intelligence landscape: our research in summarySocial Data has a very favorable outlook…

It is seen as a data source with promise. Only 1 out of 4 see it as a low value data source.

Social data needs some level of interpretation beyond the dashboard

Social Data users expect some level of help / interpretation to get up to speed with social solutions.

Mistaken Identity: ‘Social Intelligence’= Facebook?

As it’s currently defined, “Social Intelligence” is very misunderstood label.

Data quality is the most important feature to buyers of social data

Garbage in – Garbage out. Your analysis is only as good as your data.

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The Social Intelligence landscape: our research in summaryThe #1 use for social media data is customer engagement

It is seen less as a platform for data mining and analytics

Industry Analysts wield considerable influence over the category

Smaller companies, look to Altimeter. Forrester and Gartner are the most important influencers for larger companies.

Today, social data will not displace other data solutions.

It is complementary to other solutions and budget must be net-new, or from paring down to make room.

Our proposed definition for ‘Social Data’ is well-received

Pre-and-post measurement of our definition provides more utility in the minds of users.

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“Recently, we took a closer look at one company that is closely following this model of social integration…we do know SDL’s social intelligence tools are

advancing past most other enterprise vendors.” CMSwire

• With our research driven understanding of the competitive landscape, we have evolved our social intelligence technology and solution to deliver exactly what businesses need to get the most from social data that can be tied back to the needs of your business and customers, beyond engagement and community execution tools.

• Our Customer Commitment Framework takes social media monitoring to the next level where value is evident from our breadth of coverage, access to historical data, multi-lingual data sources and exceptional quality of data.

• Delivering compelling service and software solutions and outstanding customer support, we understand the need to make sense of numbers presented in dashboards and enable you to address the areas that impact your customers to drive the buying, sharing and advocacy behaviours that impact the customer journey and experience.

How can SDL help?

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Technology overcoming barriersComplexity – SDL technology effectively gathers only the relevant content that indicates where customers or potential customers sit on a brand, product or content journey. SDL’s heritage and success in language technologies then enables a rigorous analysis to determine the experiences that are most impactful on business success, which eliminates the time and labour necessary to structure content manually.

Action – Patented and proven algorithms are applied to structured data to provide immediate insight into performance, based on the business need. The consistent and standardised KPIs allow our clients to determine how the market is changing; how well their brands and products are performing and how well competitors are performing alongside, in near real-time.

Time – SDL technology effectively enables a near real-time view of how customers and potential customers are experiencing products, brands and content, identifying pain points quickly and enabling a diagnostic plan for the business to improve experiences. Our combined service and solution offering helps to leave you with the data that matters and tangible insights

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Applications of social data to the business

• Marketing and product teams can determine how effective a product launch will be across regions, languages and unique audiences

• Marketing teams can determine a global roll out plan based on insights throughout a product launch, marketing campaign, a brand entering new markets, a website launch etc.

• Customer experience teams can determine if the brand promise is being delivered across the entire customer journey and where barriers and enablers are

• Brand and Sales teams can determine effectiveness of partnerships and sponsorships to drive stronger and more successful partnerships or to demonstrate success to existing and potential partners

• Customer Experience teams can identify successful customer engagements that are typically difficult to assess (i.e. dealership experience for automotive or FMCG-market or manufacturer-retail)

• Marketing managers, digital experience teams and social engagement teams can evaluate campaign effectiveness and assess audience engagement across markets and competition to determine best practices

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