IDP delivers data-driven marketing solutions such as Loyalty Marketing Analytics focused on ‘invasive’ data mining and deep-dive analytics. Data-driven solutions revealing the complex interactions between loyal customers and products.
Over 30 years ago, the airlines, with air mileage programs, and supermarkets, with targeted coupons, first leveraged loyalty marketing analytics. Retaining loyal customers with rewards is not new. Retention marketing and loyalty marketing analytics are not new. The strategy today is the same, but tactically, there’s no comparison. Data volumes, data complexities and data velocities have all increased rapidly. Consumer expectations continue to evolve. Today, customers expect to be rewarded with personal and relevant offers.
And the time marketers have to respond continues to drop. Marketers are becoming more savvy, but so are consumers and competitors. So, retention marketing must be creative, engaging and actionable.
It’s critical to use all customer data at hand to find the right mix for your target audience. Seventy-seven percent of transaction-based programs fail within the first two years. Since 97 percent of loyalty programs are transaction based, getting it right matters. — business.com. Jan 2016
Loyalty marketing analytics are not rocket science, but are complex and require deep-dive, ‘invasive’ data mining. Loyalty marketing analytics use data from as many channels as available, learning as much as possible about customers including: preferences, habits, and both purchase intent and actual behavior. The analytics require both time-series (transactions) and cross-section (demographic, survey) data.
If you make it a point to listen to your customers on social media, you will have a strong understanding of what they want, need, feel, and shy away from. You will become more adept at catering to current trends. — MarketingProfs, Jan 2017
Success depends on being able to generate meaningful interactions that tell a convincing story and can anticipate customer behavior. Loyalty marketing analytics is a mix of consumer behavior and predictive analytics; it is at minimum 75% mining data for interactions and at maximum 25% analytics.
45% of customers say they will shop at a retailer again if they have a personalized shopping experience. Using data and insights, retailers can identify more personalized and relevant offers, messages and product recommendations… before customers even know they need something. — Chain Store Age, Apr 2018
Loyalty Marketing Analytics — IDP
So we remove the requirement that business analysts manage unruly data — bridging the gap between data management and analytics. Analysts focus, not on data, but on making recommendations from statistics.
We integrate disparate data sources and build rock-solid analytical data sets. We deliver actionable analytics, that not only scale, but give consistent results. Even when facing difficult data.
With IDP, marketers control their marketing technologies!