The document discusses a methodology for understanding customer journeys by connecting various data sources to analyze the interplay between offline and digital media. It employs structural equation modeling to highlight insights such as the impact of digital display on consumer engagement and the correlation between social media chatter and brand attributes. Key findings indicate that offline media supports positive consumer sentiment and that particular metrics are crucial for understanding brand alpha in relation to retail sales.

1. Connecting Disparate Data for Customer Journey Insights

2. Modelling the Customer Journey Using SEM
Key Objectives & Approach
1.Connect multiple data sources (research, media spend, social media and retails sales) to understand causal relationships.
2.Can we understand the journey of offline media versus digital media?
3.What place do social media display banners play in the wider insight eco-system compared with the master-brand and category brand Semantic Engagement IndexTM (a social consumer engagement metric developed using Linguistics – slide 5)
4.Is there any salient concepts we can use to help us drive online conversations about brand Alpha? Our approach to understanding this involved developing Structural Equation Model (SEM) – a method commonly used in social science to connect disparate statistical models and gauge the importance of latent (unobserved salient) concepts. We created a path model to display the results.

3. Structural Equation Modelling
Correlation is significant at the 0.01 level (2-tailed)
Correlation is significant at the 0.05 level (2-tailed)
Consumer engagement as a lower funnel metric within the brand Alpha insight ecosystem
TOTAL COMMS AWARENESS BRAND ALPHA
BRAND ALPHA MASTERBRAND NET POS SEITM
BRAND ALPHA
RETAIL SALES VOLUME
0.56
BRAND ALPHA
ENGAGED SOCIAL MEDIA VOLUME
0.25
0.21
INSTORE
TV
DIGITAL DISPLAY
TOTAL BRAND AWARENESS
0.15
0.33
0.201
BRAND ALPHA
NET POS SEITM
0.45
CARES FOR YOU
MAKES YOU HEALTHY
WOULD RECOMMEND TO OTHERS
0.21
0.34
0.40
0.16
RADIO
SOCIAL MEDIA
DISPLAY
PRINT
~ 1 Week Lead
0.05
OUT OF HOME
Causal relationship
Co-varying relationship
Brand Alpha Media Spend
Brand Alpha Tracking (% or % endorsement)
Net Positive Semantic Engagement and Engaged Volume
Retail Sales Volume for brand Alpha
LEAVES YOU SOFT & SMOOTH

4. The Role of SEITM within the brand Alpha Insight Ecosystem
Key Insights
1.Offline media transmits through to positive consumer chatter via awareness channels.
2.Digital display is strongly associated with consumer engaged volume for brand Alpha on social media.
3.Positive social chatter about brand Alpha is strongly linked with agreement on intrinsic brand Alpha attributes (including likelihood to recommend) from survey based tracking.
4.The net SEITM (positively engaged consumer chatter) is positioned closer to retail sales as opposed to social media display which is more of an upper funnel metric, driving brand awareness.

5. About Us
The Semantic Engagement Index (SEITM) is a product of Stance-Shift AnalysisTM*. Published and peer reviewed, Stance Shift AnalysisTM reveals what really matters to the consumer. This is the underpinning of our approach to measuring social media commentary. Stance-Shift measures consumers’ verbal shifts in positioning as they talk, where the “shift” infers a landmark change in emotion, intensity, appraisal and commitment towards a subject (brand, topic, campaign or concept) This approach enables us to solve for what others miss: Size, Trend and New Concepts. Two levels of scoring:
1)Emotion and Commitment is understood through engagement scoring – far superior to simple words/comment frequency commonly used to create “sentiment metrics”.
2)Adaptive tonality scoring (the + and -) to understand negative and positive sentiment. The Semantic Engagement Index SEITM integrates our Stance Shift measurement engine to power consumer insights and advanced analytical modeling.
The Semantic Engagement IndexTM
Stance Analysis: Social cues and attitudes in online interaction, Mason, et al, Linguistic Insights

6. Michael Wolfe CEO Bottom Line Analytics Global E: mjw@bottomlineanalytics.com M: 770.485.0270 www.bottomlineanalytics.com
Masood Akhtar
Managing Partner, (EMEA)
Bottom Line Analytics Global
E: ma@bottomlineanalytics.com
M: +44 7970 789 663
www.bottomlineanalytics.com