If you have friends who work in retail, don’t expect to see them until the New Year. The numbers are staggering. According to the NRF’s forecast, holiday sales in 2015 are expected to represent approximately 19 percent of the retail industry’s annual sales of $3.2 trillion. However the holiday season – defined by NRF as November and December – can deliver as much as 30 percent of a retailer’s annual sales. Talk about a race to the finish.
To capitalize on this massive opportunity, retailers with budgets to match often test a number of new marketing techniques around this time, especially around Black Friday. Retail brands dominate the holiday airwaves (my current favorite is Sainsbury’s revival of Mog the Cat which brilliantly combines the right level of nostalgia and entertainment – and you don’t even have to be British). But in addition to these traditional media blitzes, marketers try to maximize sales with targeted online promotions, personalized recommendations, in-store beacons, co-marketing and affiliate programs, and a host of other ways to make sure they reach the right customer at the right time with the right message to drive sales.
The proof is in the numbers, right? Whoever beats their sales numbers at the turn of midnight on December 31st wins? Certainly that’s how investors and the media generally measure it, as if a retailer was a box office hit or miss. However, this narrow focus on end of year sales numbers overlooks the potentially immeasurable gift that the season really provides retail marketers – the data they collect during their holiday campaigns and the potential to strengthen engagement with their customers long-term.
Now, imagine a world where, at the end of the holiday season, retailers were also ranked based on the number of actionable customer insights developed. Imagine if January and February were seen as critical months of the year – the time when your advanced analytics elves toiled in their big data workshops integrating the wealth of customer data collected during the holidays and building models that help tell compelling stories. Imagine if they were able to accurately report back what worked and what didn’t work, resulting in stronger sales year-round, improved customer relationships, and retailers that were better prepared to ramp up customer engagement going into the next holiday season. If I were a retail marketer, that’s the world I’d want to live in.
But here’s the rub. Collecting and then integrating data into a big data environment alone won’t automatically drive valuable customer insights. In order to understand the patterns of a complex and multi-channel marketing strategy, your teams will need to connect the dots across multiple variables and sources, extracting insights from large volumes of data, both structured and unstructured – and do so in a way that unequivocally maintains consumer privacy.
Measurement is widely acknowledged as the single hardest piece of the marketing puzzle, and it’s becoming more difficult as the marketing ecosystem continues to evolve and grow. Building a measurement model you can trust when most marketing teams are using scores of technologies, tools, platforms and applications is potentially the largest challenge facing brands today. But there are a few steps marketers can take to improve their effectiveness.
Integrate the most powerful data, and no more. To marketers, the idea of having such a vast array of sources to feed analytics and enable measurement is both exciting and overwhelming. However, the integration of all these sources – from your own structured marketing data to unstructured social media feeds – is complex. And the collective price tag of all this data can strain your budget. First, validate the data sources that have the best potential to impact your pre-determined business objectives. Then apply a filter and focus on integrating the high priority data to achieve breakthrough measurements reflecting what is happening as a result of your marketing efforts.
Adopt a people-based approach to data. In a mainly digital landscape, marketers are faced with a number of watch-outs. The ratio of cookies to devices fluctuates, especially as fraudulent bots increase. Not only does it hinder a single customer view, but it also can cause double, or even triple counting in your measurement. You can improve the accuracy of your measurement by taking a people-based approach. This resolves multiple instances of a consumer across devices and cookies down to a single instance and can be achieved by using knowledge-based match network technology that supports identity resolution. With a people based approach, you get a real single view of your customer and reduce duplication in your measurement as well as modeling and journey mapping. You’ll have a solid foundation for high statistical confidence, and you’ll know all of the attributes of the data without knowing an individual identity.
Take advantage of Safe Haven technology. Marketers today are living in two separate worlds – the world of known customer information and the world of anonymous online information. But, in order to truly determine your cross-channel effectiveness, such as determining whether online campaigns contributed to offline sales, you need to bring those worlds together, without compromising the privacy of your customers. With the volume of velocity of data coming from the online, cookie-based world, the only way that you can view all channels together for your measurement analysis is make ALL the data anonymous. Safe Haven technology can link this data safely and privately, anonymizing the data while retaining all of the linkages in the data for analysis.
As with any race, the adrenalin rush helps competitors get to the end, and psychologically that pressure may be necessary for retailers of all sizes to meet their year-end goals. But if marketers are unable to learn from the experience of the holiday rush and using insights to improve marketing activities year-round, they may be missing out on the biggest holiday gift of all.