Analytics

What it means

Analytics is the critical practice of translating sets of data and information into actionable stories and insights to inform effective decision-making. The first step is to identify quantifiable goals and key performance indicators (KPIs), which are then used to measure success and serve as guideposts for managing and optimizing future actions. It is also helpful in challenging assumptions by providing empirical evidence to support a strategic direction instead of relying on anecdotal information.

Harvard Business School offers a helpful way to categorize the four basic types of analytics organizations typically use: descriptive (reports current performance), diagnostic (articulates the “why” behind data trends), predictive (forecasts trajectory), and prescriptive (plans actionable strategy).

How it’s used

Museum marketing, communications, and audience engagement teams use a combination of some or all of the types of analytics described above, depending on their institutional goals and technological infrastructure.

• Descriptive analytics entails measuring progress against KPIs, such as comparing current visitation numbers or email open rates relative to preset goals.
• Examples of diagnostic analytics include examining seasonality or market trends to explain attendance fluctuations or identifying patterns across compelling email subject lines that prompt high open rates.
• An example of predictive analytics is harnessing behavioral data of customers across digital marketing to identify a target audience or to re-engage those who responded to an advertisement or email.
• Prescriptive analytics might use a Customer Relationship Management (CRM) system, such as Salesforce, and apply algorithms to assign a value or “score” to different museum audiences in their customer database, based on their touchpoints or interactions throughout their customer journey. (See also Audience Journey.)

Because museums are human-centered institutions, it is important to note that while critical, analytics do not tell the whole story. Qualitative methods of gathering and interpreting data, such as interviews, focus groups, and observational studies, can help provide a fuller picture than analytics alone.

Why it matters

Understanding audiences—both in person and online—at every point of their engagement before, during, and after their museum visit can be powerful in charting the long-term sustainability of a museum—in terms of both mission and revenue.

Data-informed storytelling and communications can be potent guides for decision-making, and the right mix of analytics can help the museum convert its data into actionable insight.

Notes

See also Metrics and Audience Journey

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