Posts Tagged ‘database marketing


Case Study: How Harbor Sweets uses customer data effectively

Harbor Sweets is a Massachusetts-based gourmet chocolate company that offers a variety of premium sweets. In 1973, the company emerged from humble beginnings when Ben Strohecker set out to create the “best piece of candy in the world.” The result was Sweet Sloops, a sailboat shaped piece of almond butter crunch, covered in white chocolate dipped in dark chocolate and crushed pecans. Over the years, the company grew to feature additional candy lines and retail outlets across the U.S. Harbor Sweets also added a significant mail-order catalog division.

Their catalog program was successful in delivering sales during key holiday buying seasons, but the company also wanted to ensure that holiday campaign mailings – the main driver of catalog business – were maximizing sales.Harbor Sweets needed a solution that would efficiently turn existing customer data into actionable next steps. Essentially, Harbor Sweets wanted to find out if removing a single mailing to “active customers” from the holiday mail schedule – which included mailings every month from September through December – would conserve marketing resources, while refraining from negatively impacting revenue or overall response rates.

Harbor Sweets conducted a suppression test, assessing how effective the holiday campaign mailings had been at driving sales. Harbor Sweets mailed the catalog to everyone in December and ran a suppression test for September, October and November. The results were surprising.Harbor Sweets was actually hurting sales by mailing too many catalogs to customers during the holiday season. The results also found that the cadence for the catalogs could be reduced to three, while still achieving similar results.

Additionally, Harbor Sweets learned firsthand that it is imperative to be open to analyzing data and customer behavior in new ways.The more information available on existing customers, the more effective the software is in its results, whether it is predicting customer’s next steps or customers at risk of defection.

The results allowed Harbor Sweet to develop a long-term marketing process for the future. The revenue saved by removing one mailing is now applied to another mailing during non-peak times to provide customers with a more effectively targeted, timely catalog.

Source: DM review


Building brand agility thro’ customer insights and integrated marketing techniques

A slow economy does not always mean death-knell for brand marketers. The ones who mine customer data, identify purchase patterns and discover useful insights will be the ones who will win in this environment. At Cequity, we continue to advice companies to walk this path with 3 specific strategies:

  1. Accelerate your customer database management strategy
  2. Embed analytical thinking within marketing teams where use of data & analysis is made mandatory
  3. Micro-market – Identify smaller & smaller segments and increase campaign velocity with relevant offers

Here’s what the article has to say:

According to Experian, companies that can gain useful customer insights through integrated marketing techniques will benefit from greater agility than their competitors and will be able to more quickly adapt to market changes and provide products, services, and value propositions that are more closely tuned to customer needs and purchasing patterns.

Collect insights, not just data
According to Marie Myles, director of marketing consulting at Experian’s Integrated Marketing division, “Based on our experience with some of the world’s largest consumer brands, the turbulent economy simply means a re-doubling of efforts to derive even more valuable intelligence from every consumer interaction.”

Actions for brand growth

  1. Understand customers and their needs
    Customer insight needs to be continually revisited to ensure that it is up to date, focusing research investment on this area and not solely on the brand. Marketers need to use this intelligence to create engaging and relevant messages based on a solid understanding of each customer’s preferences, needs and behaviours. This will pave the way for true one-to-one communication and enhanced brand loyalty.
  2. Analyse and segment
    Customer profiling, clusters or RFV models are essential to identify which customers are spending the most, how to uplift sales and to detect high value customers that show signs of diminishing value. As new trends emerge, marketers can use this insight to adapt and refine retention marketing techniques on a personalised basis.
  3. Adapt products and services
    It is imperative to assess the environment and for marketers to re-evaluate their propositions. In a changing economic climate brands need to be responsive to evolving buying habits. By taking this approach, marketers will be able to offer a better service to customers, making it harder for competitors to lure them away.
  4. Integrate channels to increase customer engagement
    Customers expect to be contacted through different media. Companies need to understand these media links and weave different online and offline messages to build compelling, engaging and personal experiences. Integrating channels at different stages of the customer buying cycle and customer management programme will drive benefits including a more consistent and persistent message.

Data Warehouse can wait- Start with Data-Marts

Very often we find organizations spending a lot of time planning and less time executing. So is the case with long gestation projects like Datawarehouse. Most often, requirements keep changing, business challenges are also dynamic.

Here’s an interesting article on how enterprises must start with data marts and get some quick-wins before they move to large scale DW projects:

An Enterprise Data Warehouse is a long term commitment: There are many imperatives (or foundations), which are key for a Data Warehouse. The examples of these imperatives are foundation or conformed dimensions, fine-grained granular data, comprehensive star-schemas etc…These elements need high level of readiness and investments to build these foundations. These foundations (though great for data marts as well) can be compromised for initial set of Data-marts.

Business Learning– Initial set of data-marts will provide great learning, less on the IT side and more on the business side. Here are the set of learnings from business side:

  • Creating business themes
  • Building Data-Mart Business Requirements
  • Building Dimensional Model
  • Testing of Data-Mart
  • Taking business decisions around the extraction and transformation
  • Generating the information out of the Data-Mart through end-user tools (like reporting and analytics application)

Examples of IT Learnings:

  • Extraction, Transformation and Loading design
  • Processing Load Management
  • Handling Data Explosion (data goes up exponentially as you add sparse fields- where most of the records are blank)
  • Change Management (end-to-end impact analysis if you make a change in the Data Mart Model)

Show-case for sponsors: A successful Data-Mart makes sponsorship of a Data Warehouse much easier.

Quick-hit: A Data-mart is a quick hit and gives earlier gratification.

Non-Disruptive: It does not take away the attention of an organization from other big things


Taming the data beast

In a world where the quantum of data that’s being captured is increasing leaps and bounds, how do companies make sense of these huge piles of data? It is imperative that data must be converted to simple, easy to interpret visual methods at speed.

In this article, Angela writes:

Moore’s Law has driven quantum leaps in the processing power of software and hardware systems. Organizations have become larger and more complex. Demands for up-to-the-minute access to data have intensified.

he most effective way to tame the data beast is through interactive visualization. Spreadsheets and tabular reports are at their limits. Utilizing visual metaphors allows multiple dimensions of the data to be understood at once. In context, it provides a “narrative” for the data. Interactivity allows the user to engage the data in his or her thinking process, which enables a dynamic dialogue with the data.

By empowering knowledge workers with visual tools and hands-on access to data, they can find patterns, distributions, correlations or anomalies across multiple data types. Users can select data elements, filters, highlighting and display options to change data perspectives – from high-level overviews down to the lowest levels of detail. The visual cues inherent in the software enable a deep exploration and understanding of the data set at hand.

Read more

At Cequity, we believe customer intelligence will be the biggest competitive advantage enterprises will have in the next decade or two. Successful enterprises of tomorrow will be the ones who can organize and leverage this information at speed to optimize their marketing performance, increase accountability, improve profit and deliver growth. Cequity insights will bring to you trends and insights in this area and it’s our way of sharing best practices so as to help you accelerate this culture and thinking in your organization.
May 2018
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