Author: annaktaylor

Your Real Ambassador – Design

Posted on by annaktaylor

Design is a vital piece of the Marketing spectrum, influencing an audience by evoking thoughts and emotions and driving performance. A brand expresses itself through design, aiming to attract and engage people for whom the visual experience is resonating and appealing. 

Most of the information that we process is optical, which means that our ability to create powerful designs is essential to our communication capabilities.

 

Elements of Design

  • Hierarchy, Symmetry and Direction
  • Text Placement
  • Typography Styles, Weights, Sizes
  • Layout, Format and Sizing
  • Use of White Space and Line Leading
  • Images, Graphics and Shapes
  • Effects and Animation
  • Colors, Lightness and Shades
  • Icons, Indicators, Gestures, and Symbols
  • Balance, Alignment and Proportion
  • Contrast, Emphasis and Repetition
  • Lines, Patterns and Textures
  • Commonalities, Groupings and Variety
  • Rhythm and Harmony

The practice of design requires the following:

  • A clear objective and a defined outcome
  • Definition of the dominant expression, mood or emotion
  • Knowledge of the intended audience and what they gravitate to
  • Simplistic initial draft with the ability to scale up
  • A foundation that is guided by space, contrasts and alignments
  • Assess each aspect of a design for value, prominence and appropriate placement
  • Eliminate constraints and complacency by getting out of the proverbial box to challenge your creativity
  • Test versions of a design with specific differences (i.e. color schemes, layouts, messaging, CTA) to assess response levels
  • Embrace that visual messages are more likely to be consumed than excessive content
  • Randomness can be confusing – create a reliable flow and progression

 

Most essential is to bring passion to your designs and cavort with your imagination! 

Showcase your work and be willing to hear the feedback, both favorable and critical. Of importance is to understand that design is subjective and based on partiality. We cannot deny personal preferences. With that in the forefront of your mind, allow opinions to be shared with recognition that their input is not a judgment, simply a viewpoint.

Design is powerful and persuasive. Give it magnitude. Structure your production process to give design the wherewithal to be discoverable, flexible, visionary, effectual, artistic and a paramount expression of the brand.

Data Science for Marketing

Posted on by annaktaylor

Many people believe the terms machine learning, big data, AI, neural networks and data science are interchangeable. There are distinctions to each that will be critical to understand in order to tactically architect your data-driven programs.

Data Science is a discipline that involves the study of data and the methods used to capture, store and analyze in order to mine valuable insights and unearth patterns, correlations and other key understandings.

Big Data involves the systems and processes utilized to manipulate, manage and analyze high volume and complex data sets.

Machine Learning encapsulates the algorithms and statistical models that computers apply to data to execute tasks, forecast outcomes or identify trends, patterns and precedents.

AI (artificial intelligence) is the growing science of machines demonstrating intelligence using information from which it learns, reasons and makes independent corrections.

Neural Networks are a system of algorithms, considered to be somewhat configured like the human brain, designed to find patterns by processing, interpreting, labeling and clustering data points.

Data is meant to be action-oriented with a value extraction. Data science involves several areas of expertise including data engineers, analysts, researchers and designers.

Common goals are to create pathways to problem solve, reach peak performance, develop business tactics based on sales patterns, garner project insights or other defined objectives.

Essential to any data science initiative is to evaluate the usability and application of the results to ensure its benefit and ROI.

Cloud computing has significantly advanced conditions and accessibility for data science to be utilized by companies of all sizes.

Data science is designed to handle, optimize, manipulate and effectively manage the four Vs of information:

     1. Volume [quantity]
     2. Veracity [quality and accuracy]
     3. Variety [range of types and diversity]
     4. Velocity [speed]

Important Considerations

• Data frame sets and structure – look at whether the data is standardized and labeled or raw and unstructured

• Throughout any project, there will be requirements for data cleansing, processing and refining

• With the understanding that there are numerous variables within data, several iterations and validation of outputs are necessary

• Evaluate patterns, classifications and correlations using predictive or prescriptive practices

• Don’t underestimate the time and resources required for preparation, standardization and cleansing of data to make it actionable.

• Pay close attention to ethics, privacy rights, regulations and other critical factors when utilizing data and know when you must expressly share sources and obtain informed consent.

While data science may appear to be vast and dense – there is a viable blueprint for developing a practical and scalable application that can powerfully serve your company by providing otherwise unknown insights. Grasp the opportunity to make data a fundamental tool that can drive far more formidable strategies – giving you a real boost in competitive positioning and smart spending.

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