Commentary

Leveraging Big Data And Getting Personal With Cross-Pollination Marketing

by Mike Lees , April 22, 2014

Many organizations turn to cross-pollination marketing, which leverages two brands to help customize and personalize the marketing experience for customers. Specifically, cross-pollination refers to the innovation and spark that is created by bringing fresh eyes, distinctive perspectives and common goals together. In order to most effectively use cross-pollination marketing, companies must also incorporate data analytics to ensure that they are appropriately targeting both existing and potential customers and creating partnerships that make sense to reach them.

The insight and intelligence gained through accessing big data enable you to understand that your customers and prospects are real and important. Data adds context and flavor to the marketing mix, allowing for very personalized communications and targeted campaigns. When considering a partnership, it’s more important than ever to be data savvy. The alignment of your data and data-based strategies with that of your partner is what will reap results.

Cross pollination can be a great strategic weapon but only if developed in a thoughtful and practical way. The key is to be data driven and to use analytic insights to drive the relationship—the relationship between partners as well as the relationship with the consumer.

In order to achieve the results you want from a co-branding or co-marketing partnership, consider these actions: Firstly, think creatively about the products or services that complement yours and that will enhance the appeal or credibility of your offering. Use data to prove that you are targeting the same or a similar audience. Secondly, use your joint commitment to data-driven methods to tailor your messages and offers so they are both personal and relevant. And finally, be prepared with engaging follow up and nurture. With an influx of new leads, you will need to provide engaging content and compelling messaging to influence behaviors.

Take Fairmont Hotels and Resorts and Lexus – they teamed up to provide Fairmont President's Club members (their loyalty program) access to Lexus hybrid vehicles as hotel courtesy cars to transport guests around town. It was the perfect solution for Fairmont to provide a greater level of personalized service to guests during their stay.

For Lexus, it was a great way to expose an affluent audience to their brand and line. They were the first to market with this idea. For both companies, it was a win. It showed their commitment to the environment, which helps grow loyalty and retain their clientele. It was co-marketing at its best. By using customer intelligence, it combined the strength of their marketing dollars and brand names and potentially led to an increase in each company's market share.

The concept of cross pollination can be exciting and can lead to successful partnerships. Unfortunately, when approached without careful thought, preparation and analysis, such a venture may not live up to expectations. Many marketers believe they have a solid grasp on who their customers and prospects are, what motivates them to make purchase decisions, and how they wish to engage with the brand. Far fewer can back up those beliefs and assumptions with evidential data. To create and execute effective marketing campaigns, a brand must differentiate its customers and prospects based on levels of affluence, interests, behaviors and other personal attributes.

A mutually beneficial partnership is dependent on the same level of segmentation and personalization. Each partner must come to the table prepared. Know your customers. Know your audience. Know their habits, behaviors, interests and demographics. With a solid understanding of each partner’s buyer personas and target audience, the companies can quickly determine if they are a “fit” in sharing specific or overlapping market segments.

Further analysis is needed to create an effective co-branding or co-marketing campaign. While the business partners may share a target audience, it has become abundantly clear that consumers are individuals and want to be known and treated as individuals. The one-size-fits-all days of mass marketing are over. Whether you are considering co-branding or co-marketing partnerships, your business stands to gain a lot. Your efforts will only be as effective as your ability to speak directly to consumers – your current customers, your partner’s current customers, or new prospects. The key is to get personal.

affluent, data management, data-targeting

2 comments about "Leveraging Big Data And Getting Personal With Cross-Pollination Marketing".

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David Shor from Prove, April 23, 2014 at 1:04 a.m.
Mike,
I appreciate the effort you put into writing articles for the benefit of all. I feel this one misses the mark bigtime. You use click-bait techniques to reference big data but talk nothing about it except "use data."
You can do better amigo.
David
Reply

Mike Lees from WealthEngine, April 24, 2014 at 4:13 p.m.

Thanks for the continued dialogue on my post. The use of big data in marketing is an important conversation worth having. I would make a couple of points in response.

Marketers are never short of creative ideas, and I agree that in the case above, the idea for a hotel to partner with a car provider is fundamentally a solid one that a smart marketer could have devised regardless of whether it was informed by data. But how do they select which car provider to associate with and in which locations? Only an understanding of the data would have highlighted that Fairmont customers have a strong affinity to Lexus. My more general point though is that marketers have a greater opportunity than ever to use cost effective, personal-level data to support or even validate their creative ideas. Gut feel just doesn't cut it anymore in an era where marketers have to justify their expenditure in the board room using solid data. And, it's not as if marketers have only just started spending money on data - market research has been a mainstay for us for decades but is an expensive option (compared to big data solutions) and gives only market level data.

I can genuinely say that I did not have any 'click bait' motives in mind when I wrote this piece…..in fact, I had to go and look up it's meaning when I read this comment! If 'click bait' means 'provoking thought with a short piece that warrants further discussion' then I plead guilty! My goal was to raise an idea that many may not have considered and not to give a deeper instructional perspective on the mechanics of the data itself.