Gerhard  Brink

Gerhard Brink

1624786020

Make Better Decisions with Data-driven Personas

Over the years, personas have been great tools to support user experience. These fictional characters catered to identifying the needs and problems of different segments of people. However, with time, their importance decreased. This is because relying merely on generalizations wasn’t helping companies to grow. The companies saw that these personas did not influence the decision-making process. It was soon realised that these personas lacked interactivity.

The situation seems to be have changed now. With data analytics in place, personas using big data can now be generated. A combination of interactivity and analytics opens the door of interactivity as a persona is no longer limited to being a static, flat file. As the preferences of one user varies with that of the other, personas catering to the same are no longer a distant dream. Data-driven personas hold the potential to adapt to different preferences, choices and demographics of the users. Such an interactive persona can be deployed in a variety of fields – marketing, HR, healthcare and design to name a few.

That said, what garners the attention of people across the globe is the concept of APG – Automatic Persona Generation (APG). This is considered to be an excellent tool to turn data into personas. This data-driven system is a blend of analytics metrics, foundational data and conceptual persona. Considering the fact that the user population has varied interests, the tool aims at generating casts of personas and each segment of the user population having a persona. APG stands the potential to identify the unique behaviour pattern of the users.

APG generates casts of personas representing the user population, with each segment having a persona. Relying on regular data collection intervals, Data-driven personas enrich the traditional persona with additional elements, such as user loyalty, sentiment analysis, and topics of interest, which are features requested by APG customers. This is followed by associating these unique patterns to demographic groups based on the strength of association to the unique pattern. It is now time for matrix factorization to come into play. Using this technique, latent user interaction is determined.

#big data #latest news #make better decisions with data-driven personas #personas #data-driven #better decisions

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Make Better Decisions with Data-driven Personas
Gerhard  Brink

Gerhard Brink

1624786020

Make Better Decisions with Data-driven Personas

Over the years, personas have been great tools to support user experience. These fictional characters catered to identifying the needs and problems of different segments of people. However, with time, their importance decreased. This is because relying merely on generalizations wasn’t helping companies to grow. The companies saw that these personas did not influence the decision-making process. It was soon realised that these personas lacked interactivity.

The situation seems to be have changed now. With data analytics in place, personas using big data can now be generated. A combination of interactivity and analytics opens the door of interactivity as a persona is no longer limited to being a static, flat file. As the preferences of one user varies with that of the other, personas catering to the same are no longer a distant dream. Data-driven personas hold the potential to adapt to different preferences, choices and demographics of the users. Such an interactive persona can be deployed in a variety of fields – marketing, HR, healthcare and design to name a few.

That said, what garners the attention of people across the globe is the concept of APG – Automatic Persona Generation (APG). This is considered to be an excellent tool to turn data into personas. This data-driven system is a blend of analytics metrics, foundational data and conceptual persona. Considering the fact that the user population has varied interests, the tool aims at generating casts of personas and each segment of the user population having a persona. APG stands the potential to identify the unique behaviour pattern of the users.

APG generates casts of personas representing the user population, with each segment having a persona. Relying on regular data collection intervals, Data-driven personas enrich the traditional persona with additional elements, such as user loyalty, sentiment analysis, and topics of interest, which are features requested by APG customers. This is followed by associating these unique patterns to demographic groups based on the strength of association to the unique pattern. It is now time for matrix factorization to come into play. Using this technique, latent user interaction is determined.

#big data #latest news #make better decisions with data-driven personas #personas #data-driven #better decisions

Uriah  Dietrich

Uriah Dietrich

1618521240

Only Data-Minded Marketers and Market-Minded Developers Can Achieve Data Driven Marketing

Using data as a part of your marketing plan can have a tremendous impact on your overall results, which is why data-driven marketing has become the standard for many agencies.

However, data-driven marketing may require many businesses to rethink the way they work, especially when it comes to cooperation between their various teams.

You may have heard about the concept of collaboration and automating processes before - something referred to as webops. Now an increasing number of companies are throwing marketing into the mix.

Among the most important factors is a close working relationship between marketing and web development teams if a business wants to make the most of data-driven marketing.

#data-driven #data-driven-marketing #web-development #marketing-data-science #teamwork #data-driven-development #data-driven-decision-making #webops

Ian  Robinson

Ian Robinson

1623813810

Filtering Data to Deliver Improved Data-Driven Decisions

Data cleansing or scrubbing is a form of data management. Although over the years, businesses accumulate a lot of personal information; ultimately, information becomes outdated. For instance, more than ten years one may change address or name, and then change the address again.

Data cleansingt is a process in which you go through all of the data within a database. And you require removing or updating information that is incomplete, improperly formatted, duplicated, or irrelevant. It typically involves cleaning up data compiled in one area. While data cleansing involves deleting information, it is focused more on updating, correcting, and consolidating data to make sure your system is effective as possible.

The data cleansing process is generally done at once; however, it can take a while if the information has been piling up for years. That’s the reason why it’s essential to perform data cleansing regularly.

#big data #data management #latest news #filtering data to deliver improved data-driven decisions #filtering data #data-driven decisions

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Gerhard  Brink

Gerhard Brink

1622611140

83% Of Data-Driven Organisations Gained Critical Business Advantages During Pandemic

Tableau Software has announced a new study developed in conjunction with YouGov, to explore how organisations in the Asia Pacific and Japan (APJ) have used data during COVID pandemic. The survey noted that data-driven companies in India are more resilient and confident during the pandemic, compared to non-data-driven companies.

According to the data, 83% of data-driven companies in India have reported reaping critical business advantages during the pandemic. Along with that, the survey revealed that 62% of organisations believe that leveraging data can provide multiple and vast benefits to businesses, including more effective communication with stakeholders. Another 58% organisation noted making faster strategic business decisions with 56% witnessing increasing cross-team collaboration. Further, the data stated that 48% of organisations have managed to make their business more agile.

Being data-driven is also allowing organisations to be more optimistic towards this turbulent time. The survey stated that around 76% of organisations are confident and looking forward to a promising future for their business.

While data-driven companies are reaping its benefits, the non-data-driven companies are facing massive challenges in grasping the importance of data. This demonstrates the prevailing disconnect of how businesses leveraging data and the potential for organisations to benefit from a more data-driven approach.

#news #data advantages #data driven companies #data driven decisions india #data driven organisation #data driven organisations gained advantage amid pandemic