Data is useless unless it leads to actionable insights
Most companies are awash in customer data, whether they know it or not. Like a flood, it flows through, around and past the organization. This data can come from both online (digital) and off-line (non-digital) sources. Usually, only some of it is captured. Much of it is missed. Data analytics are often superficial.
Consider the possible sources of information about your customers:
- Purchase data
- Customer service
- Dealer data
- Industry databases
- Demographic appends
- Website behavior
- Social Media and more
We know from decades of experience that the most successful companies take a structured approach to gathering relevant data from these and other sources. But this is only one step. To be useful, data must provide actionable insights that can be used in subsequent customer engagements. This means it must be tied as much as possible to individual customer records, and accessible to sales, marketing and customer-service staff throughout the organization.
Holistic Customer Profiles
Here is where a robust CRM system is essential. Only when customer data from both online and off-line sources is aggregated into holistic customer profiles (or customer master files) can a company begin to develop a full picture of every customer – their entire history of engagement with the company, their preferences, wants and needs – and make this picture available to whoever needs it on their team.
Actionable Data Analytics
This picture, in turn, is unhelpful and incomplete without analysis that generates insights about customer behavior, needs and preferences. Only with these insights can the organization understand how to optimize each customer’s experience in future interactions. Many organizations are reluctant to invest in sophisticated analytics, based on perceived cost or complexity, or simple lack of awareness of the possibilities:
- Look-alike modeling
- Opportunity Sizing
- Acquisition Modeling
- Lead Scoring
- Cross-Sell and Next Best Offer
- Retention/Survival Modeling
- Response Modeling
- Customer Lifetime Value (CLV)
As you can see from this list, there is no shortage of data analytics opportunities. These and other new technologies, tools and techniques make deep understanding of individual customers and customer segments more accessible than ever before.
At the end of the day, the goal is to pull together all relevant off-line & on-line data, tie it to individual customers, analyze it for actionable insights, and then use this information to optimize each individual customer’s experience with the brand. Doing so in a meaningful way, with the right messaging, at the right time, through each customer’s channel of choice completes the cycle of Closed-Loop Customer Engagement. Learn more about this final stage in our next post.
Barton Goldenberg explains Closed-Loop CRM during his Keynote at CRM Evolution 2017.