The Power of Small Data
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The document discusses the evolution of data, emphasizing the significance of 'big data' and its complexities, including volume, velocity, and variety. It warns that big data alone is not sufficient for effective marketing, as human insights and intuition are essential in interpreting data and making business decisions. The document suggests starting small by identifying data sources, determining key performance indicators, and continuously testing and adjusting the approach based on insights gained.
The Power of Small Data
- 1. 11 The Power of Small Data
- 2. 1980’s 1990’s 2000’s 2010’s Present Megabyte Defining Big Data Kilobyte Gigabyte Terabyte Petabyte Site hits Site hits New Analytics Data New Analytics Data New Analytics Data Social Data Social Data Social Data Site hits Site hits Unstructur ed Data
- 3. 33 Defining Big Data Volume of Data • Explosion of data sources especially social • Tera/PetaBytes of data warehouse Velocity • Frequency of data collection • Social streams / real-time and geo-sensor Variety of Data Sources • Multiple disparate data sources • Transaction • Owned / Un-owned data properties Insight • Segmentation • Intersection
- 5. 55 Big Data is Not the Holy Grail for Marketers Risks • Amplifying quantifiable perspectives at expense of valid and real human intuition Not Fully Automated • No black box • Human error, invalid data, inaccuracies • Complex to create intersection, deal with large volumes of data Human Insight • Needs process, KPIs and metrics • Needs human interaction to interpret
- 6. 66 Big Data is Not the Holy Grail for Marketers
- 7. 77 Identifying Small Data Segmentation • Filtering by slices (time, geo, profile, etc) • Intersection of multiple data sources Measure things that are important • Outliers and trends • Watch for out of context data The Last Millisecond • Ability to collect data to create information that allows you to make better business decisions • Insight to effect the decision at the right moment
- 8. 88 How Do You Start? Plan and Start Small ID Data Sources • Site Analytics • Social Streams • Transaction • Un-Owned Determine KPI Metrics • Cross-references / intersection of data • Measure key data points often in an aggregate manner Leverage Technical Tools • ETL • Aggregation, reporting Define Your Target and Goals • Segmentation of audience • What slice of data needs to be analyzed Test and Adjust • Analyze trends, outliers using analytics and graphical tools • Refine – learn what works and does not and make adjustments
Editor's Notes
- #5: Source: http://www.gartner.com/technology/research/digital-marketing/transit-map.jsp