Optimized Marketing through Intelligent Social Media Analytics!
Posted by statsoftsa
Real-Time Analytics for Sentiment Analysis, Marketing, and Media Mix Optimization
Plugging into the Instant Feedback Loop
The marketing of brands and products has dramatically changed. Fewer key messages are disseminated through printed media, radio, and TV because of the delayed response to the campaigns days, weeks, or even months later. Instead, marketing campaigns today begin with a careful consideration of which specific web portals, search providers, social media, or blog spaces to target, and how to effectively communicate the message.
The Instant Echo Chamber
Consumers today have a voice, and they have the instant media to make their voice heard. As a consequence, any confusing marketing messages or missteps will instantly affect the blogosphere, discussion groups, and social network sites, as the “buzz” quickly emerges in the echo chambers of the world.
This means that consumer responses expressed via web media can provide immediate feedback to your marketing team:
- To provide an accurate forecast of expected sales
- To identify problem areas, unexpected barriers, or any pushback
- To match refinements to the messages and echoing from the mix of media to improve marketing efficiency
Recognize the Link:
Marketing > Buzz > Sales
The basic challenges are clear:
- How to determine which marketing channels to choose and how much to spend on each channel in order to reach your target audience
- How to link marketing activities to sentiment expressed by consumers on relevant web sites, blogs, discussion groups, social network sites, etc.
- How to link a reliable index of sentiment, or complex multivariate indices of consumer response and effect, to subsequent product sales
- How to put it all together to predict the expected success of an optimized marketing campaign based on the immediate feedback from consumers
Putting It All Together: Predictive Modeling
The STATISTICA Enterprise solution for Social Media Mix Optimization provides an integrated system that is as responsive as the market and the messages reverberating through the web-based echo chambers themselves.
Bringing Data Pieces Together
Social media response is obtainable in many formats and aggregations: from the users count, number of views, friends, or “Likes” that can be available daily, hourly, or even by the minute, to time stamped customer reviews that may not be updated as frequently. Configuring and maintaining all data sources in STATISTICA Enterprise and numericizing text fields with STATISTICA Text Miner combined with STATISTICA ETL (Extract, Transform, Load) functionality helps to solve this challenging task in an efficient and automated way.
STATISTICA Data Miner and Predictive Modeling
The analytic engine driving the system is the STATISTICA Data Miner library of capabilities and algorithms, which builds accurate predictive models for linking variables from different sources.
The long-established Data Miner program is the most comprehensive, best tested, and universally acknowledged most versatile platform for predictive modeling, offering options for manual model building and configuring complete workflows within a visual programming environment.
STATISTICA Text Miner
This program provides the high-capacity engine for indexing unstructured user-generated content (text) to extract the critical dimensions defining relevant sentiments expressed across multiple web sites, blogs, and social media sites efficiently and reliably. STATISTICA Text Miner equally serves the following purposes: meaning extraction, automatic text categorization, entity extraction, bringing unstructured data to numeric form, and concept extraction with Singular Value Decomposition (SVD).
This system provides the robust and scalable server backbone for automating the analytics, linking marketing expenditures to consumer sentiment, and linking consumer sentiment to expected demand (and sales). STATISTICA Enterprise also provides the display layer to manage large numbers of channels via efficient and hierarchically nested dashboards that will alert/alarm when undesirable trends are detected.
Optimizing the Media Mix
Once a complete system is in place that reliably tracks the relationships between marketing expenditures and customer sentiment, the system can be optimized using powerful “what-if” scenario analyses to identify the optimal combinations of expenditures for different advertising and marketing channels. Predictive models will be built to establish confidence regions around the formula for the optimal mix to empower marketing or product managers to evaluate risk/reward scenarios, and ultimately, turn the buzz into sales.
Key Features Summary
- Central Configuration and Management
- Data Connections, Aggregation, and Alignment across different departments within organization. Data configurations are stored as metadata and serve as templates for subsequent analyses and analytic workflows
- Automated, Proactive Alerts
- Measure Marketing Success and Sales Conversion in one Platform
- Final Solution can Embrace Data Collection with Data Historian Functionalities or be Easily Integrated with Existing Infrastructure