Use Predictive Analytics to Harness Big Data Power

Predictive analytics, meaning scientific analysis that leverages customer and donor data to predict future prospect and customer actions, can scientifically "cherry-pick" names from overwhelming "big data" lists and other files. For example, at AccuList, experienced statisticians build customized Good Customer Match Models and Mail Match Models to optimize direct mail results for prospect lists, as well as one-on-one models for list owners to help acquire more new customers or donors. Plus, predictive models can aid other marketing goals, such as retention, relationship management, reactivation, cross-sell, upsell and content marketing. One of the benefits of analytics is improved lead scoring, for example. Lead scoring is too often a sales and marketing collaboration, in which salespeople provide marketers with their criteria for a "good" lead and marketers score incoming responses, either automatically or manually, for contact or further nurturing. Predictive analytics will remove anecdotal/gut evaluation in favor of more accurate scoring based on data such as demographics/firmographics, actual behavior and sales value. It also speeds the scoring process, especially when combined with automation, so that "hot" leads get more immediate contact. And it allows for segmentation of scored leads so that they can be put on custom nurturing tracks more likely to promote conversion and sales. In fact, with predictive analytics, list records can be segmented to achieve multiple goals. The most likely to respond can be prioritized in a direct mail campaign to increase cost-efficiency. Even more helpful for campaign ROI, predictive analytics can look at the lifetime value of current customers or donors and develop prospect matching so mailings capture higher-value new customers. Predictive analytics also can tailor content marketing and creative by analyzing which messages and images resonate with which customer segments, identified by demographics and behavior, in order to send the right creative to the right audience. Finally, analytics can develop house file segmentation for retention and reduced churn, looking at lapsed customers or donors to identify the data profiles, timing inflection points and warning signs that trigger outreach and nurturing campaigns. Data analysis and modeling can also be used to improve future marketing ROI in terms of channel preferences and even product/services development. Of course, reliable predictions require a database of clean, updated existing customer or donor records, which AccuList also supports via its list hygiene and enhancement services. For helpful links, see https://www.acculist.com/predictive-analytics-harnesses-data-for-marketing-roi/

Why You Should De-dupe Your Data

Anna Kayfitz, CEO of StrategicDB Corp., recently offered AccuList USA this expert advice on why direct marketing success requires de-duping data: 

In today’s data-driven marketing, data is not only the most important asset that your company can have but can also make or break your campaign. Having clean data impacts not only marketing activities but also impacts your reputation, operations and decision-making. De-duping is one of the most important aspects of overall data hygiene. Duplicates can be found on many levels of data; they arise at the household level, individual e-mail level or company level. If you are not convinced that you need to de-dupe, consider the following five benefits. First, you can avoid different offers to the same customer. For example, you send two different direct mail creatives to the same household. As one of the records was a customer, you decided to provide a returning customer 15% off, while the other record was marked as a prospect and only got 10% off. Now the person opening both direct mails will be confused by having two different discounts, and the company also can face a PR nightmare. Second, you can cut unnecessary cost. For example, assume you are doing a direct mail creative which costs you $5 per mailing. Your list contains 10,000 recipients. The total cost of mailings therefore is $50,000. If you decided to de-dupe, you would find out that 10% of your mailing list was duplicated. Therefore, $5,000 was a waste of resources. It would have been much cheaper to de-dupe prior to deploying your campaign. Third, you will get better analytics for decision-making. Analytics is important not just from a perspective of understanding how your marketing and sales is performing but also from a decision-making perspective. By having duplicates in your CRM, you are going to be double-counting your list capabilities, miscalculating your true growth rates, and getting the wrong rate of responses. If you are looking to make a decision on future campaigns, basing it on duplicate data will will give you the wrong list count, wrong budget and possibly the wrong creative picked (especially if you are basing it on an A/B testing done previously). Next, de-duping helps prevent customer service confusion when clients call in, e-mail or come into the store. For example, Mary Smith is found twice in your CRM with the same phone number. She calls in to your customer support to inquire about her order status. Your customer service rep decides to pull up the customer account by phone number and finds two records. Now she has to put the customer on hold while she checks both accounts to try to locate the last purchase before she can even assist the customer. Not only is it wasting everyone’s time and making customer service inefficient, it also makes the customer have a bad customer service experience. Finally, the biggest impact that duplicates have on your business is a potential loss of sale. If you have duplicates, you do not have a true view of all prospect or customer activities. Therefore, you could be excluding prospects from a sales call because your lead scoring system indicated that they are not ready. However, if the data from both records was combined, you would have all signals indicating they are ready to be passed on to sales. With duplicates, by the time you figure it out, a customer may have already lost interest and gone with your competitor. De-duping should be part of your data-cleaning initiative, either prior to any major campaign or on a yearly basis. You can easily de-dupe your list by using a de-duping tool that will require less effort to identify duplicates and establish a master record than is required to deal with the consequences of duplicate data. For more help, see http://www.acculistusa.com/why-you-should-de-dupe-your-data/