In this perspective manuscript, my co-authors and I propose an approach of employing personas as an alternative form of making large volumes of online user analytics information useful to end users of the user and customer analytics, with results applicable in software development, business sectors, communication industry, and other domains where understanding online user behavior is deemed important.
Toward this end, we have developed a system that automatically generates data-driven Personas from social media and online analytics data, capable of handling hundreds of millions of user interactions from tens of thousands of pieces of content on YouTube, Facebook and Google Analytics, while retaining the privacy of individual users of those channels.
Our approach (1) identifies and prioritizes user segments by their online behavior, (2) associates the segments with demographic data, and (3) creates rich persona profiles by dynamically adding characteristics, such as names, photos, and descriptive quotes.
In this research, we propose a novel approach for isolating customer segments using online customer data for products that are distributed via online social media platforms. We use non-negative matrix factorization to ﬁrst identify behavioral customer segments and then to identify demographic customer segments.
We employ a methodology for linking the two segments to present integrated and holistic customer segments, also known as personas. Behavioral segments are generated from customer interactions with online content. Demographic segments are generated using the gender, age, and location of these customers.
In addition to evaluating our approach, we demonstrate its practicality via a system leveraging these customer segments to automatically generate personas, which are ﬁctional but accurate representations of each integrated behavioral and demographic segment.
Results show that this approach can accurately identify both behavioral and demographical customer segments using actual online customer data from which we can generate personas representing real groups of people.
In research led by Joni Salminen, we conceptually examine the use of personas in an age of large-scale online analytics data.
Based on the criticism and benefits outlined in prior work and by practitioners working with online data, we formulate the major arguments for and against the use of personas given real-time online analytics data about customers, analyze these arguments, and demonstrate areas for the productive employment of data-driven personas by leveraging online analytics data in their creation.
Our key tenet is that data-driven personas are located between aggregated and individual customer statistics.
At their best, digital data-driven personas capture the coverage of the customer base attributed to aggregated data representations while retaining the interpretability of individual-level analytics; they benefit from powerful computational techniques and novel data sources.
We discuss how digital data-driven personas can draw from technological advancements to remedy the notable concerns voiced by scholars and practitioners, including persona validation, inconsistency problem, and long development times.
Finally, we outline areas of future research of personas in the context of online analytics. We argue that to survive in the rapidly developing online customer analytics industry, personas must evolve by adopting new practices.
Brand Discovery: Uncover how your core customers feel about your product or service and how they rationalize the purchase decision.
Channel and Offering Alignment: Align every piece of offerings and marketing activity to a persona and purchase stage, identifying new channels and needs where opportunities exist.
Communication: Personas are also great for communication among team members and across departments. Personas are GREAT for meetings! They keep folks focused on the BIG picture.
Content Creators: Content creators can leverage personas for the delivery of content that will be most relevant and useful to their audience. When planning for content, we might ask “Would Bridget understand this?” or “Would Bridget be attracted by this?”
Executives: can keep personas in mind while making strategic decisions. In fact, a persona can become a “silent member in the boardroom”.
Experimentation and Optimization: Carry out well-thought experiments to produce statistically significant business insights and apply the results to optimize performance.
Journey Mapping: Plot the stages and paths of the persona lifecycle, documenting each persona’s unique state of mind, needs, and concerns at each stage
Marketing: When you understand where your core customers spend their time online, you are able to focus your marketing spend on these channels.
Persona Discovery: Document the individuals involved in the purchase process in a way that allows decision makers to empathize with them in a consistent way.
Product Managers: can use the information to design a product that meets the needs or desires of core customers, and marketing can use personas to craft messages that resonate.
Product Offerings: Personas can be extremely helpful in product development. With the help of personas, you can more easily build the features that suit your customers’ needs. Forrester Research reports a 20% productivity improvement with teams that use personas.
Reporting and Feedback: Report and review data and insights to drive strategic decisions, as well as provide information to the organization as a whole.
Sales: Targeted offerings can help you convert more potential customers to subscribers, followers, and customers. You can also use persona description to tailor lead generation which is likely to improve your lead quality and satisfaction.
A persona profile is the end product of the persona creation process. A common layout of a persona profile that is usually 1 page containing a textual description and typically one photo. The textual description will include, along with humanizing elements such as name, demographic information (e.g., education, job, age, etc.) and behavioral information (e.g., interests, goals, purchases, etc.).
Creating a persona involves five steps, which are:
Step 1 Identify: Categorize the population of customers, users, or audience members
Step 2 Collect: Gather data about the Identified populations specifically concerning behaviors (or goals, pain points, etc.) and demographics.
Step 3 Segment: Group the population into unique segments based on unique behaviors, goals, pain points, etc.
Step 4 Generate: Produce identifiable complete segments with combined behavioral and demographic data
Step 5 Enrich: Augment each complete segment with individual characteristics, such as photo, name, etc. to create a complete persona profile for each segment. The set of persona profiles that represents the population is the end product of the process.