Optimize lets you take a larger pool of targets and compare them to a complex set of rules to find the best candidates for a particular offer, considering not just the local data available within a single campaign, but data across multiple campaigns, taking into account business constraints at a much higher level (for example, outbound call center capacity). In other words, Optimize can help you maximize your marketing across your entire business, not just for a single campaign or offer. Since Optimize works across campaigns, you can prevent customers from being over-contacted and lower the probability that those valuable customers will opt-out from further communications or simply dispose of your communication without reading it. Starting with a larger initial selection expands your opportunities to reach previously under-resourced segments of your customer base, while also maximizing overall optimality within your business constraints.

You configure Campaign to select targets for your marketing campaign from your customer data. This selection process can be very simple:

all female customers

or more complex:

all female customers between the ages of 25 and 45 who earn over $45,000 a year, have purchased your product in the last 90 days, and have not been contacted for at least 30 days

However, in any marketing organization that is product- or offer-centric, multiple campaign designers are competing for the best targets for their product or offer. This often raises the following challenges:

Cross-campaign collision—Cross-campaign collision occurs when multiple campaigns target the same customer. For example, if you have two campaigns, one person creating a mortgage refinance offer for people who have recently moved to a new home and another person creating a free online banking offer for people who have recently opened accounts. It is highly probable that many of your customers might be targeted for both campaigns.

Customer fatigue—Repeatedly contacting the same customers, leading to decreasing response rates over time. Many of your best customers are good candidates for virtually any offer. Campaigns commonly overlap in their target selection by selecting from your top-tier and/or most loyal customers.

Missed opportunities—Some customers may be satisfactory candidates for an offer, but are consistently ignored by the current selection process.

For example, consider the following scenario:

One member of the marketing team creates a campaign that identifies high-value customers based on recent use of loyalty cards at the stores in his region. Customers that meet these criteria are sent tickets to a private invitation-only sales event at a small set of larger stores.

Another member of the marketing team creates a campaign that identifies high-margin customers based on significant spending through the Web site channel. Customers that meet these criteria receive a special online-only coupon the next time they login to the online store.

Yet another member of the marketing team creates a campaign that identifies top-tier customers based on the long-time and consistent use of loyalty cards and correspondingly high spending habits. Customers that meet these criteria receive special mailings with in-store coupons.

Many of the customers will probably be targets for at least two, if not all three of these independent marketing campaigns. Excessive contact might drive away some business, or cannibalize success of one marketing campaign at the cost of another. For example, if a high-value customer received both a web coupon and an in-store coupon, the customer might spend the same amount of money regardless, resulting in a wasted contact and a lower response rate for one of the campaigns. Worse yet, sending out a 15% off coupon and a 20% off coupon to the same customer for the same time frame will surely result in a lower-than-expected response rate from the 15% offer. To combat the fatigue issue, you may have different business rules such as "only four email contacts are allowed in any one-month time period" or "at least 14 days must elapse between direct mailings." However, since individual campaigns do not interact with each other, this strategy does not support other guidelines, such as "customers who receive the invitation-only sales event offer cannot receive the in-store coupons."

Companies that have evolved to customer-centric (for example, segment-based) marketing largely avoid these types of offer conflicts, since a single individual controls the entire stream of communications to the customer segment. This segment-based approach has its benefits, but it is typically a difficult and time-consuming process for a company to change from a product-centric to a customer-centric marketing organization.

With Optimize, you create a set of constraints or rules that address all three of these situations to determine the best candidates for each across the whole of your customer pool. Using the Max # of Packages rule, you can limit the number of offers a customer receives. Using the Never A with B rule, you can enforce that no one receiving the invitation-only sales event offer receives any coupons. Each marketer determines a score for each offer. Optimize optimizes the contacts, providing the surviving list of contacts that satisfy the specified rules and constraints. The marketers then extract the contacts for their offer and complete their campaigns, each campaign reaching out to the globally optimized set of best customers.