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Customer Insights

Deeply knowing your customers is essential to developing strong relationships and maximizing customer value

Many businesses struggle to really know their customers.  It’s not uncommon for companies to treat all their customers the same despite having different needs, economic value, product, and customer experience desires.  Many struggle to determine how to allocate marketing resources to drive profitable, organic growth.

Kinship Consulting provides the insight needed to acquire, target, and retain your most profitable customers.

Our Services

 

Do you really know your customers?

Kinship Consulting delivers the deep customer insights that allow you to really understand your customer base.  We know that your customers can differ on economic potential, needs, expectations, values, and behaviors. Recognizing these differences is a critical step in building an effective customer strategy and customer experience.

Deploying the most appropriate qualitative and quantitative market research techniques, Kinship Consulting is able to answer the such questions as:

  • What does our current and target customer base look like?
  • Which customer groups offer the greatest lifetime value?
  • What are their needs and expectations?
  • Where is the optimal customer value created in the overall customer journey?
  • How should we best segment our customers?

We help our clients target the right customers, seize the right opportunities and ensure that they will realize the full economic potential of their products, services and relationships.

Our capabilities include:

  • Customer profiling and segmentation
  • Qualitative and and Quantitative Market Research
  • Ethnographic and Behavioral Psychology
  • Market and Competitor Analysis
  • Human-based Design
  • Marketing Effectiveness and ROI
  • Data Mining and Predicative Models
  • Customer Lifetime Value/ Loyalty Economics
  • Product Concept Testing/ Value Propositions
  • Brand positioning and health

 

Get deep insights from your data

Winning and retaining customers requires using data and advanced data science analytics to develop the appropriate marketing strategies.

Deploying sophisticated data mining and predicative statistical modeling, we help companies grow customer value by accelerating the “path to purchase” and deepening customer relationships through:

  • Advanced segmentation strategies to help identify the most profitable customer segments and enhance marketing effectiveness;
  • Predicative modeling and text analytics that can be used to help you:
    • Increase customer retention through the development of customer churn models;
    • Optimize marketing spend and ROI through the development of marketing response models
    • Develop the right customer strategies based on customer lifetime value.
    • Predict increased customer share of wallet.

 

Project Experience and Case Studies:

Develop a needs-based segmentation model of the consumer finance market

Situation: Deeper customer understanding was needed within the mortgage purchase, refi, and home equity product lines to drive direct response acquisition and retention marketing effectiveness.  Action:  Developed a needs-based segmentation model of the consumer finance market through detailed quantitative research and statistical modeling.  Seven distinct segments with were identified, sized,and prioritized.  Detailed personas were developed including media preference , channel preference, key values, communications positioning. Current customers were included in the sample with appended behaviorial data in order to create scoring algorithms to map customers to segments. Outcome:  Key target segments were identified based on economic potential, highest predicated response rate, and value propositions.  Segmenation models were incorporated into marketing campaigns which lowered direct response mass-media and direct mail marketing cost per leads, achieved higher response rates and enabled more effective communications messaging

Developed predicative models for direct response campaigns

Situation: Leading energy company sought to grow market share organically within certain CTA levels.  Direct mail campaigns were being deployed without specific targeting criteria or predicative response models. Action:  Applied marketing analytics, customer profiling, and segmentation to direct mail campaigns through the development and application of propensity models.  Predicative models were developed  for net sales with no churn within two months. Outcome: Significantly improved net sales, lowered costs to acquire, and resulted in an over 100% improvement in net sales yield rate.  Predicative models worked in 80% of campaigns employed.  Able to effectively determine campaign ROI and effectiveness of decile segmentation.  Indicated opportunities for further enhanced customer targeted to higher value customers, and higher ROI by redeploying marketing investment to more profitable segments.