Customer-based forecasting: Get an edge with new shoppers

The current economy and increasingly demanding consumers are making retail planning and forecasting a more daunting task than ever before. To deal with these challenges effectively, retailers need some key information. Is there access to the customer data you need, when you need it, across all of your touch points? Are new, emerging customer segments appropriately represented in your projections? Are old traditional segments overrepresented?

With the answers to these questions, you can develop customer-based forecasting capabilities that instill confidence in revenue-related forecasts, and inform marketing decisions aimed at driving revenue growth, especially in a slumping sales environment.

Understanding new customers is an important part of this forecasting. With the right steps, you can improve intelligence and gain deeper insights into future customer behavior that let you more profitably reach this segment.

1. Study new customers
An important and often overlooked part of any sales forecast is an analysis to determine if new customers exhibit different buying patterns (and potential value) than established customers. New customers need to be separately studied to project future behavior and then combined with similar forecasts for established customers as part of the overall analysis. Are your forecasts based on outdated assumptions about customer behavior?

2. Reach new shoppers early
The number of past-month shoppers is a common and important metric used by many retailers. Recently, many retailers are experiencing serious declines in the percentage of these frequent shoppers as customers either delay or decide against future purchases. Exacerbating the problem of fewer shopping visits is a trend to shopping at fewer stores.

Retailers struggle with customer frequency metrics, since shopping habits are often difficult to change once established. What’s needed are programs aimed at new customers early in their relationship, before their shopping habits with your brand have settled in.

3. Track by cohorts
There are bottom-line turnaround benefits in identifying the percentage of new customers who can be persuaded to change their expected purchase behavior. Start by developing a month-by-month analysis that groups first-time customers together as cohorts, so that the percentage of the group returning to shop each subsequent month is tracked and measured.

The cohort analysis will identify differences in past-month shopping incidences across channels, time frames and seasons, all of which can lead to smarter marketing communications aimed at entrenching shopping habits that will benefit your brand for years afterwards.

4. Profit from new insights
A new shopper tracking capability leads to a range of other insightful analysis, such as:

• Percentage of new shoppers spending more;
• Percentage of new shoppers spending less; and
• Changes in the repurchase cycles among new shoppers.

As an example, shopping center and soft-goods retailers have found that monthly shopping incidence is strongest among the two youngest shopper segments (i.e., ages 18-24 and 25-34) and tends to increase along with household income. If you sell in these categories, are you systematically flagging new customers to your brand from these segments? Consider how tracking their activity each month as a cohort group and maintaining year-to-date spending behavior on your database could help pinpoint specific opportunities to provide incentives to shop more frequently.

David King is CEO of Fulcrum, New York City (fulcrum-mktg.com) a leader in advanced analytics, technology and multichannel program solutions for marketing. He can be reached at dking@fulcrm.com.