This very moment your customers are painting a vivid picture of their behavior, preferences, and intentions. And they’re doing this by simply going about their daily lives, leaving a digital landscape of data through web, social, apps, mobile, their cars, product use, and service interactions. For a marketer this data is a goldmine.

Big data, behavioral analytics and social listening are shining new light on your customers. Absolutdata delivers comprehensive Customer Analytics services for global brands large and small, to understand the consumer journey and drive marketing actions through acquisition, growth and retention.

  • Case study 1
  • Case study 2
  • Case study 3

THE 360 DEGREE CUSTOMER VIEW

Draw a more accurate and vibrant picture of your customer by blending behavioral analytics with traditional and unstructured data sources. 360 degree modeling works best with an omni-channel approach, reaching across touch points to render customers based on a much richer information set.

  • Know your customers from all touch points
  • Create detailed personas with the NAVIK Converter tool
  • Map the digital footprint across mobile and online
  • Understand key consideration drivers
  • Predict intent to buy with social listening
  • Influence customer behavior with deeper insights
  • Discover distinct new microsegments
  • Case study 1
  • Case study 2
  • Case study 3

MICRO SEGMENTATION AND BEHAVIORAL ANALYTICS

Machine learning techniques are adept at identifying patterns as they emerge. It’s now possible to move beyond a static snapshot of a few segments to dynamic micro segmentation. Pattern recognition also displays consumer behaviors that can help you be more relevant.

  • Predict potential customer actions
  • Identify the best campaigns for individual customers
  • Develop user personas and archetypes
  • Segment users based on patterns and behaviors
  • Build a behavior-driven customer experience
  • Use the NAVIK Converter tool to do this for you
  • Case study 1
  • Case study 2
  • Case study 3

CUSTOMER ENGAGEMENT STRATEGIES

Customer loyalty is the heart of the customer life cycle. Engaging customers over time requires strategy, technology and commitment. Marketing, sales and support must work together to create an effective data-driven approach to nurture and monetize the customer connection.

  • Create microsegments to personalize the experience
  • Communicate via preferred channels at the best times
  • Identify topics and content that solve customer pain points
  • Understand loyalty program drivers
  • Anticipate what customers will research or buy next
  • Incent customers to be advocates with high value offers
  • Case study 1
  • Case study 2
  • Case study 3

CUSTOMER ACQUISITION ANALYTICS

Take the guesswork out of converting prospects with advanced analytics and technology. Learn what consumers buy, why they buy it, and when. Then delve into the journey of building a strong healthy customer base.

  • Create hyper-personalize offers to maximize conversions
  • Predict intent to buy with social listening
  • Analyze past campaigns to make better offers
  • Anticipate next best actions by microsegment
  • Identify messaging that addresses pain points
  • Track prospect awareness, consideration and intent
  • Case study 1
  • Case study 2
  • Case study 3

CUSTOMER LIFETIME VALUE (CLV) MODELING

Predictive and behavioral analytics allow businesses to quantify and forecast the value of individual customers across time, product lines, segments and even channels. The ability to identify and curate high value customers brings clarity to marketing strategies and initiatives.

  • Allocate marketing spend more strategically
  • Design programs to accelerate monetization
  • Identify high value prospects
  • Rank high-to-low value customers
  • Gauge loyalty program upgrade potential
  • Ascertain customer intent to re-purchase
  • Case study 1
  • Case study 2
  • Case study 3

CUSTOMER RETENTION AND WIN BACK

Losing a customer is costly, so early churn prediction and prevention are worth the investment. But churn happens. In the event of customer loss, advanced analytics can help drive laser focused win back strategies.

  • Pinpoint churn risk factors with predictive models
  • Tier retention offers based on predicted customer value
  • Detect dissatisfaction patterns to mitigate exposure
  • Analyze existing data to discover new win back offers
  • Profile lost customers with high win back potential
  • Case study 1
  • Case study 2
  • Case study 3

CUSTOMER SATISFACTION ANALYSIS (CSAT)

In the era of the empowered customer, mobile and social media have magnified the already dominant impact of word of mouth. Play an active part in boosting customer satisfaction by using big data analytics to glean a new awareness of CSAT drivers and nurture healthy customer relationships.

  • Develop services based on customer needs
  • Analyze incoming customer data to ensure positive experiences
  • Find and fix the root causes of poor customer feedback
  • Measure the impact of interactions on each customer’s satisfaction score
  • Leverage your loyalty program to find CSAT drivers