“Normal is changing …. Again” – Amazon.com

As the technology sector moves into 2013, across nearly all product, solution, and services categories, companies continue to face increased competition, more sophisticated and digitally connected customers, and global markets that exhibit fundamentally unique buyer dynamics.  At the same time, there is a proliferation of customer-centric information – leading to a number of big data challenges (e.g., how to turn data into insight, people/talent gaps, organization and role clarity issues) but balanced by a tremendous opportunity to drive significant incremental value (e.g., better targeting, offer/pricing refinement, real-time incentives, higher levels of customer satisfaction and retention) by developing meaningful customer insight. While there continue to be significant advancements in traditional customer research and predictive analytics (“big” data or otherwise), both information latency and the related challenges around developing insights given the rapid pace of change is putting tremendous pressure on organizations.  As a result, companies are struggling to move from having an abundance of data and frequently disconnected and/or stale research towards creating integrated, timely, and ultimately more actionable customer insight.

However, like most potential drivers of competitive advantage, there is not a “one-size-fits-all” approach to developing meaningful customer insight.  Businesses must consider understanding customer needs in the context of their go-to-market model, specific strategies, and the decisions insight may inform.  As an example, in the consumer space where the need for dynamic insight versus latency gaps are often greatest – coupled with rapid data proliferation driven by the explosion of social media – companies must increasingly manage a massive volume of feedback and be able to react “real-time” to brand, product, and service issues.  In the B2B space (e.g., enterprise software) where the pace of change may be somewhat less dynamic and where product and purchasing cycles are evolving at a different pace – there is still an abundance of new solutions that are driving different account needs, satisfaction requirements, utility pricing models, and an overall shift in consumption behaviors.  While it is not an either/or decision, companies need to align insight strategies and investments to best support business model requirements and product lifecycle pacing – from early stage idea generation (or front-end of the innovation funnel) through to customer experience/relationship management – while using the right balance of monitoring, customer research and feedback, and data analytics.

Insight Generation Opportunities within the B2C Space

For companies and retailers playing in the consumer space, the penetration of mobile technology, explosion of social media, improved economics of collecting and analyzing customer data (particularly “big data”), and the availability of new insight capture tools and techniques – combined with the decreasing cost and commoditization of traditional customer research – are  driving the most rapid changes around how insight is being captured and analyzed (and where challenges around insight latency are most substantial).   Increasingly, companies are seeking to:

• Better leverage abundant and distributed social media sources:  For example, monitoring, listening and targeted “troving”
• Utilize new research tools and techniques:  For example real-time experience tracking, online communities/panels, consumer labs, social media diaries, consumer neuroscience and biometrics, co-creation/joint innovation techniques, ethnography
• Effectively design and align data analytics with business need across massive and potentially separate customer data sets:  Analytics and predictive modeling across multichannel purchasing/transaction, customer service and experience, Customer Relationship Management (CRM), Customer Experience Management (CEM), pricing/revenue/profit, and customer feedback and satisfaction data in the context of any big-data initiatives
• Balance mix of internal and outsourced capabilities:  Research vendors, external market and customer data sources, digital agencies and outsourced analytics relative to internal customer insights resources and capabilities. Exploring different make/buy scenarios to augment requirements until net-new areas achieve scale

Effectively balancing these insight sources and capabilities, and aligning them with well-defined innovation, product development/lifecycle, and customer relationship and experience management processes can lead to breakthrough levels of highly differentiated and targeted insight development.

The Changing Dynamics of B2B Insight Development

Companies in the B2B space can also gain competitive advantage by developing more effective and timely customer insight, but given the different pace of change and nature of B2B solution and relationship dynamics, not all the next generation capabilities that are emerging within B2C space are relevant.  Since enterprise and middle market B2B relationships (and products and solutions) are significantly different relative to the buyer dynamics within consumer or small business customer segments, a different approach is required.  Key differences in B2B include:

• Multi-touch point transactions and service:  Transactional product and service interaction are often tracked across many touch points (e.g., quality, delivery, customer service experiences)
• Less relevant social media and behavior data sources:  Social media, POS payment behavior, location based tracking, and learning through “apps” are much less relevant sources of insight
• Complex relationship management:  There is often a broad, complex sales and support relationship which is operationalized differently than within the B2C world
• Complex decision making:  Customer purchase selection and decision-making can be much longer and based on complicated price-service-value tradeoffs
• Long term, contractual requirements:  Relationships often reflect long term, contractual agreements with a range of potential price and volume commitments. 

While the challenges are different and some of the leading-edge source and techniques (e.g., social listening, consumer neuroscience, online communities) may not be as useful, B2B companies can leverage the evolution in customer research techniques as well as data analytics to drive more effective insight to support strategy/innovation, product development, and customer experience management processes.  B2B companies specifically are utilizing the following:

• Automated/online research:  Traditional research and feedback can be substantially automated with online and mobile, enabling more frequent, accurate, and timely feedback
• Focused data analytics:  While the volume of customer data is a subset of the “big data” challenge,  next generation analytic tools and resources can be applied to relevant data sets (e.g., pricing, product mix) which can be particularly valuable in generating insight within both the enterprise and middle market segments
• Enterprise Feedback Management (EFM) tools:   World-class B2B companies are beginning to leverage new technologies and integrated tools to both capture and synthesize feedback and generate breakthrough insights. 

These technology-enabled EFM platforms allow more consistent, efficient, and scaled collection, analysis, and sharing of customer feedback across the organization to drive faster follow-up and more effective customer-centric decision-making.  For example real-time analysis and reporting can automatically notify a relationship manager when a customer is dissatisfied or another potential follow-up opportunity is indicated.  Additionally, feedback data and analysis can be integrated and synchronized with a company’s CRM, financial, and HR systems in order to deliver feedback in the context of other key business performance metrics and analysis driving more holistic insight and action. 

Waterstone Insight Development Experience

Successfully capitalizing on insight-driven opportunities within a data-rich, dynamic competitive environment requires that customer insight efforts must constantly evolve.  Waterstone has significant experience working with our clients to develop more effective and real time approaches to developing customer insights across a variety of business use-cases.  Regardless of the environment – B2C or B2B – we have deep understanding of how to refine, tailor, and extend insight generation processes to better inform key business decisions.  We take a customer-focused approach to all our engagements whether they require focused analysis of existing customer data (e.g., purchasing, pricing, call-center) or customized primary research to understand detailed product/feature preferences, price elasticity, or drivers of customer satisfaction and loyalty.  

In addition, we support companies in building broader, organization-wide customer insight development capabilities particularly to better align and support efforts further up the innovation funnel.  We work with clients and their partners to develop the strategy and roadmap around organization structure, resourcing (internal and external), and skills and business processes to evolve traditional market research functions into consultative, customer insight partners across the business and into the C-suite – integrating the science of research and analytics and the “art” of organization, process, and culture.

Co-authored by:

Scott Haug, Partner based out of Waterstone's San Francisco Office
Laura Green, Principal based out of Waterstone's San Francisco Office