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Bill BrunoCEO, Stratigent LLC@BillBruno

bill.bruno@stratigent.com

Allan WillePresident & CEO, Klipfolio Inc@awille

awille@klipfolio.com

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Multi-Channel Analytics

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The world we live in…

There is no shortage of data Customers are interacting with you in a variety of channels

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Rapidly Evolving

New technologies every week seemingly Solving niche problems Results in more disparate sources Double-Edged Sword

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“Big Data”?

Not an ideal representation of the task at hand There is definitely more data, but the purpose remains the same Actionable, Manageable Data Right data, to the right people, at the right time

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Organizational Challenges

Politics and Red Tape Old Processes, New Data Digital data is “not accurate” No clear “owner” as you traverse the organization Privacy

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Governance Ideals

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Automation is Critical to Success

Anything that can be automated, should be automated Frees up time for analysis and optimization

These are the tactics that drive ROI Must understand what people care about/need Build representative views for individuals/groups Accuracy/Data Validation

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Useful metrics trump actionable ones

Useful

Short-termACTIONABLE

INSI

GH

TFU

L

Long-termLow

HighMostUseful

UsefulX

The most actionable metrics are not always the most insightful.

Some metrics inform your tactics, while others inform your strategies.

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There are multiple types of metrics

TYPE OF METRIC EXAMPLE USED TO ANSWER THE QUESTION

Outcome/business driver Leads, Unique visitors How well am I doing?

Diagnostic Conversion rate How can I do better?

Smoke alarm Zero yield searches What am I doing poorly?

Predictor/Leading indicator Intent to Purchase, Intent to Use Site as Primary Resource

Will I do better?

Latent Correlations, VOC,competitive data, etc

Where is the opportunity?

*Obviously, this is not an exhaustive list.

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What kind of data is appropriate for dashboards?

• Key metrics that are directly tied to an objective, specifically key metrics that are business outcomes or high impact diagnostics

• Key metrics that have context (eg comparison to target, historical performance, meaningful segmentation, etc)

• Rankings that don’t change frequently (eg top pages)

• Rankings in which the top 10 or so aren’t sufficient to analyze (eg top 10 organic referring keywords)

• Data that is too detailed (eg paid search performance by keyword or campaign performance by creative)

Good Bad

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Top Visualizations and When to Use Them

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Top Visualizations and When to Use Them

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Data Visualization

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Why visualize your data?

Simplify consumption of complex information Assist in prioritization Engage your audience

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What makes an “effective” data visualization?

Simplify complex data sets into manageable sound bites Each visualization should answer a key question:

How is my social media performance this month? Context makes it possible to rapidly consume data

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The right tool for the job

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Ok, so how does this work in practice?

Consolidating data in the fragmented landscape…

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The reality of multi-channel data

Start with a clear sense of individual metrics Social > Web > Sales Look for correlations in data Context!

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Summarize data in a meaningful way

Ask yourself: How do all the pieces fit together? The “One visualization to rule them all” approach

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Bill BrunoCEO, Stratigent LLC@BillBruno

Allan WillePresident & CEO, Klipfolio Inc@awille

Questions?