Findability's Anand Mahurkar explains how AI can help plan, measure your social impact PR campaign

Social impact campaigns can be hard to scale and measure. Findability Sciences has recently tied up with social impact PR firm On Purpose to address that.

Anand Mahurkar, Findability

Identifying Measurement Channels 

Anand Mahurkar, CEO and founder, of Findability Sciences speaks to PRmoment  India editor Paarul Chand to explain how to define the data sets of social impact campaigns, use the insights and then measure the outcome. #Longread 

PRmoment India:  What data sets can be used to examine PR campaign outcomes?

Anand Mahurkar: Assessing the outcomes of a PR campaign for a partnership focused on social impact involves not just conventional metrics but also specific indicators that can capture the societal changes or improvements aimed for. Here are some types of data sets that can be particularly relevant:

Social Impact Metrics:

1. Impact Reach: The number of people positively affected by the social impact initiatives.

Quality of Life Indicators: Metrics that can capture changes in well-being, health, and education.

2. Sustainability Indicators: Metrics that measure how the initiative contributes to environmental sustainability.

3. Alignment with SDGs: Metrics that map the impact directly to UN Sustainable Development Goals.

Media Metrics such as Media Impressions, Reach and Sentiment Analysis.

Engagement Metrics such as:

1. Community Engagement: Measures of community involvement, perhaps in decision-making or volunteering, as a result of the PR campaign.

2. Stakeholder Feedback: Capturing qualitative feedback from stakeholders directly affected by the social impact initiative.

Digital Metrics such as Website Traffic, Social Shares, and Content Engagement.

By using a comprehensive set of these metrics, organizations can not only assess the reach and engagement levels of their PR campaigns but can also evaluate their effectiveness in achieving real social impact. Tools like Google Analytics, social media analytics, and impact assessment software can be instrumental in gathering this data.

Using AI to optimise campaign timing and reach  

PRmoment India: Can you provide examples of how AI data sets have been used to optimize the timing, reach and delivery channels of public relations campaigns?

Anand Mahurkar: While we don’t have any real examples as yet, here is how AI data sets can be used to optimize the timing, reach and delivery channels of public relations campaigns:

Timing Optimization:

1. Predictive Analytics: AI can analyze historical data to identify when target audiences are most receptive, helping to time PR releases and social media posts for maximum impact.

2. Event Correlation: AI can correlate media consumption patterns with external events (e.g., holidays, news cycles, product launches) to suggest the optimal times for PR activities.

Reach Amplification:

1. Audience Segmentation: AI algorithms analyze demographic and psychographic data to create detailed audience segments, allowing PR campaigns to be tailored for higher relevance and reach.

2. Sentiment Analysis: By gauging public sentiment, AI can help PR professionals understand which aspects of a campaign are resonating and may suggest adjustments to maximize positive exposure.

Delivery Channels:

1. Multichannel Analysis: AI can evaluate the effectiveness of various delivery channels, such as email, social media, or traditional media, to identify where PR efforts are most impactful.

2. Content Optimization: AI tools can test different headlines, body text, or images to determine what content performs best on each channel.

3. Influencer Mapping: AI can identify key influencers who are most likely to amplify the campaign’s message, helping PR professionals decide where to allocate resources.

Social Impact Measurement:

For a partnership focusing on social impact, AI can also offer:

1. Impact Tracking: Algorithms can quantify the social or environmental impact of the partnership, measuring outcomes against pre-defined goals or benchmarks.

2. Stakeholder Engagement: AI can help monitor and analyze stakeholder reactions and engagement levels, providing actionable insights for course correction.

Measuring social behaviour change 

PRmoment India: How can AI sharpen measurement of purpose-led campaigns that are typically based on behaviour change?

Anand Mahurkar: The measurement of purpose-led campaigns focused on behaviour change presents unique challenges that AI can help overcome. While traditional metrics like reach, clicks, or impressions are useful, they may not fully capture the nuanced changes in behaviour and attitudes that such campaigns aim to achieve. 

Here are some ways AI can sharpen the measurement:

Advanced-Data Analysis for Target Behavior
1. Predictive Modeling: AI can use existing data to predict future behaviour changes in the target population, providing a benchmark for campaign effectiveness.

2. Pattern Recognition: Machine learning algorithms can identify complex patterns or trends in behavior that simpler analytics tools might miss.

Enhanced Engagement Metrics:
1. Sentiment Analysis:
AI can gauge the tone and sentiment of public discussions or responses to the campaign, providing a more nuanced understanding of its impact.
2. Natural Language Processing (NLP):
AI can analyze open-ended responses, comments, or discussions to understand the public's attitude and belief changes more deeply.

Real-Time Adjustments:
1. Adaptive Algorithms:
AI can help make real-time adjustments to the campaign based on interim results. For instance, if a certain message isn't resonating, the algorithm could suggest a pivot.
2. Resource Allocation:
AI can dynamically adjust where resources are most effectively used, optimizing the campaign’s reach and impact.

Personalisation at Scale:
1. Custom Recommendations:
AI can offer personalized action steps to different audience segments, encouraging more effective behaviour change.
2. A/B Testing:
Machine learning can automatically run and analyze the results of A/B tests  (testing variations of the campaign element on different audiences to test for impact) on different campaign elements, helping to continually refine the campaign for maximum effectiveness.

Social Impact Assessment:
1. Impact Quantification:
AI can help quantify soft metrics like 'awareness raised' or 'attitudes changed' by correlating them with hard metrics such as 'actions taken' or 'funds raised.'
2. Geospatial Analysis:
For campaigns targeting specific localities, AI can use geospatial data to assess the geographical effectiveness of the campaign.

These advanced techniques can offer a far more nuanced and dynamic measurement approach, enabling campaign managers to better understand the true impact of their purpose-led initiatives

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