We talk about creating “knowledge assets” or new characteristics that can be stored on a database to help our clients understand not only what segment their customers are in, but what part of the customer lifecycle, and what that customer’s value is to the client organization as well. These knowledge assets are insights that are made actionable by marketing technology, and they really do accrue value over time. Building a roadmap for including analytics and insights is a step-by-step process.
Targeting, Analytics and Insights Milestones on the Multichannel Roadmap
1. Building Knowledge Assets with Strategic Profiling
Often the first engagement SIGMA has with new clients is to develop some customer-focused and market-focused analytical benchmarks that can be used to help make decisions about new marketing programs and help predict ROI for individual campaigns. Many clients don’t have the time to look for insights that can come from a 360° view of their customers – including bringing together both online and offline data. We are looking for characteristics such as customer lifecycle stages, customer value and customer segment. This Strategic Profiling Process begins to answer questions about customers that can drive multichannel campaign design and how you measure it.
2. Segmentation – Care and Feeding of Your Customer Segments
You may be using a segmentation system that was designed to be helpful in driving messaging tone and focus. Many clients who use systems that were developed through surveys find that the appending of accurate segment codes to their database can be problematic. There are techniques that add customer value or lifecycle measures that may enhance the ability to make a system more actionable for driving individual campaigns.
3. Campaign Targeting, Testing and Analysis
Each campaign design team needs a Marketing Analytics member who will establish a clear methodology for campaign targeting and testing for maximizing results. This member should have a mandate to check the boxes on each of these components:
- The campaign design should include a consistent Test and Learn approach that can be carried out from one campaign to the next with new learning goals building upon insights from previous campaigns. Add to this a methodology for building a business case for each campaign to forecast ROI and help with prioritization of the outstanding campaign requests.
- When the targeting and testing methodology for each campaign is established, make sure to carefully document this process for future replication.
- Develop a protocol for predictive analytics for each campaign – whether models will be created for the pilot phase, or be built on results for future stages of campaign development.
- Work closely with the creative team to build knowledge of what targeting, offers, formats, components and messages work best for each type of campaign and product.
- Of course each campaign needs an established methodology for back-end campaign analysis – which will be documented for future use and roll out.
- Establish best practices of reporting on campaigns – different types of reports for different levels of management are usually required, and this practice would be established early on in the campaign design process.
4. Integrate Online and Offline Analytics for Response Management and Attribution
As marketers seek to embrace customer engagement, their online presence takes on singular importance. Multichannel marketers need to examine how to bring direct marketing and web activity more closely together for:
- Fulfilling customers’ needs by providing immediate information personally relevant to them.
- Measuring directly attributable and personally identifiable conversion results from campaigns that cannot be easily achieved through more traditional methods.
5. Identify Opportunities for Primary Research Insights
We frequently use survey methodologies both to collect critical missing data needed to drive multichannel marketing programs, and also to build predictive analytics as well.
- Evaluate whether there is data you wished you had for campaigns, but that is not available from any source – could primary research develop that data?
- Surveys with conjoint analyses are highly useful for identifying the optimum feature and promotional mix for plans as well as prices that consumers are willing to pay for those features.
- Determine if there is a proof of concept for the use of primary research to devise targeting strategies and campaign design.
By considering these five milestones, you can incorporate customer intelligence into your multichannel campaigns and deliver both greater relevance and better results.
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