A Better Experience for Considered Purchases


Share on LinkedIn

Whether it’s a young couple buying their first home, new parents purchasing life insurance, or soon-to-be empty nesters securing a loan for their college student, considered purchases are big ticket items that involve a high degree of financial and emotional risk. They require time and forethought, and for most consumers, plenty of comparison shopping. According to Pew, 81% of Americans say they rely on their own research when making significant purchases and use online search as their leading source of information.

So how do digital marketers develop engaging customer experiences when purchasing decisions are more complex than a quick impulse buy? The key is going beyond static demographic details and using real-time consumer behavior to inform personalization.

The Right Message at the Right Time

Unlike demographics, behavior changes. Behavioral data can help identify where a customer is on their shopping journey and allows marketers and sales teams to respond to buying intent versus canned messaging based on assumptions. With real-time data, companies can deliver targeted messages that reflect a specific moment in time. And with the right tools in place, this process can be automated to scale.

Today’s consumers have come to expect this level of personalization – particularly those that will be making the majority of purchasing decisions in years to come. Nearly half of U.S. consumers ages 18-24 and 40% of 25-34-year-olds told Capco they would share their smart device data with an insurer in exchange for better personalization.

Soon personalization will no longer be a competitive advantage, but the cost of doing business. In the meantime, poorly timed messages may do more harm than good. In mortgage lending, for example, a settlement checklist could overwhelm a first-time homebuyer just learning about the benefits of pre-qualification.

Behavioral data is especially helpful for considered purchases, which often span weeks or months and where comparison shopping on lead generation sites is typical. To continue the mortgage example, a first-time homebuyer may spend weeks gathering information and visiting multiple websites before ever filling out a lead form, much less a mortgage application. In the end they may finally decide to engage with a few potential lenders through a site like NerdWallet, due to the convenience as well as the perception of a neutral third-party endorsement.

Third-party behavioral data from these sites connected to a company’s CDP (customer data platform) or CRM can provide a holistic view of a prospect’s behavior across the web. It can also help reduce customer acquisition costs by identifying high quality leads and reduce churn by notifying marketing and sales teams when existing customers are looking around. A study by Forrester found that companies combining first- and third-party behavior to inform their acquisition, retention, and cross-sell efforts generated a combined ROI of 191%.

Best Practices for Lead Management

When customers spend considerable time researching their purchasing decisions, relying on a company’s own first-party data is insufficient. Yet in some circles, third-party lead generation is unfairly treated with distain. Even the term “lead” is becoming a four-letter word. The truth is lead generation has taken on a negative connotation because some publishers use aggressive and deceptive tactics to take advantage of consumers as well as lead purchasers.

Low-quality leads – including leads that are old or recycled, fraudulent, manufactured, or manipulated – drain resources and skyrocket the cost of customer acquisition. On the other hand, companies that follow a few simple lead management best practices can optimize their costs by identifying the highest-quality leads and invest more resources into engaging with customers in a way that feels helpful rather than intrusive. These practices include:

1. Dig deep into lead quality

Marketing and sales teams must select their data partners carefully. Not only should data be accurate and timely, but there should be a sense of transparency between both parties from the onset of an agreement. Lead generators should be willing to disclose characteristics that impact the value of a lead, like whether they are being shared with competitors.

For most considered purchases, it’s also critical to know lead age. “Speed-to-lead” measures the time between a prospect expressing interest and a salesperson’s response. Harvard Business Review’s Response Management Study confirms the faster a lead receives a response, the more likely they are to convert. Alternatively, some organizations have found success focusing on less competitive, lower-cost aged leads. It’s important to keep in mind that lead age should not measure the time elapsed since the brand received the lead, but rather from when the consumer first submitted their inquiry.

It can also be helpful to understand the level of customer engagement – how long did the consumer spend filling out the lead form? And did they fill it out themselves or was it completed by a call center representative? Finally, lead purchasers shouldn’t assume duplicate leads refer to the same inquiry. Duplicates can also originate from consumers who have made multiple inquiries, which could be indicative of high purchasing intent.

2. Learn as much as possible about your customers

Studying aggregate third-party data can reveal trends about the typical consumer shopping journey and being able to match these trends with lead characteristics can help determine the best timing for outreach. For example, a look at auto insurance data revealed:

  • Millennials had a lower frequency of website visits than baby boomers across their auto insurance shopping journeys.
  • Single folks appear to have slightly more active shopping journeys.
  • Consumers with college experience have a lower frequency of site visits compared to those without.
  • The lowest shopping frequency was observed in the Pacific Northwest and the highest in the Southeast.
  • Consumers with “good” credit are less active compared to consumers self-identifying as having “poor” credit.

Understanding behavioral patterns can also help qualify and prioritize leads. When brands can identify and act on opportunity demonstrated by real-time behavior, they can optimize how much to pay for a given lead and avoid wasting resources on leads that are not likely to convert.

3. Prioritize consent to build trust

Last but certainly not least, considered purchases often involve contacting consumers directly, so it’s critical brands in these industries comply with privacy regulation to avoid legal ramifications. Courts have maintained that both lead generators and purchasers are responsible for confirming a consumer’s consent to be contacted. But seeing consumer privacy exclusively through the lens of risk mitigation is short-sighted. Since trust is at the center of every positive relationship, consent is a prerequisite for every positive customer experience.

This process begins by only partnering with lead generators who can demonstrate they’ve secured the consumer’s permission to be contacted. Fortunately, lead quality and compliance go hand-in-hand. When a consumer is ready to move forward in their shopping journey, they will want to hear from people who may be able to help them. Conversely, consumers who haven’t completed a lead form (or who filled one out six months prior) have not demonstrated a strong intent to buy.

By definition, considered purchases are complex – but they don’t have to be complicated. High-performing brands qualify their leads to optimize their resources, know that data privacy serves their interests as much as the consumer’s, and above all else, personalize each customer’s experience to reflect real-time behavior.

Matt Stone
Matt Stone is the head of marketing at Jornaya, a Verisk Business and leading data partner for the insurance and mortgage industries. Matt has 25 years of experience driving loyalty, online acquisition, and revenue for SaaS start-ups and global technology brands. Prior to joining Jornaya, Matt held executive roles at Photon, 1E, and Real Capital Analytics. For more information, visit www.jornaya.com .


Please use comments to add value to the discussion. Maximum one link to an educational blog post or article. We will NOT PUBLISH brief comments like "good post," comments that mainly promote links, or comments with links to companies, products, or services.

Please enter your comment!
Please enter your name here