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Data - personalization - engagement
Shopper and loyalty data provide a solid foundation for building relevance and personalization which, in turn, drive customer engagement
How do you get your customers to engage? Typically, shoppers connect when they feel their needs will be met or their problems solved. This can be as simple as offering an affordable price point, providing recipes to help plan meals for the week, or offering technology to make life easier. Sparks of engagement have the greatest chance of igniting when your content is relevant. Shopper and loyalty data hold the key to relevance: understanding what will be important to each shopper and creating an appealing, personalized, and timely experience.
People can - and do - change their shopping behavior. Knowing buying patterns, or what triggered a past purchase or response, are powerful predictors of the choices customers may make in the future. Data can unlock many shopping secrets by applying the right combination of technology and predictive analytics. To truly drive personalization, and hence engagement, it is important to mine data as close to the critical customer action as possible, thereby reflecting the speed of evolving buying decisions and maintaining relevance. But mining data can, at times, seem like an overwhelming task.
Addressing data overload
Data is without doubt an invaluable resource in the quest for personalization, but digesting, refining, and leveraging something which continues to grow at an exponential rate presents its own challenges. In fact, by 2020 about 1.7 megabytes of new information will be created every second for every human being on the planet* - to put that in perspective, two minutes of video streaming is about 1.7 megabytes. Failure to tackle it could adversely affect the ability to drive personalization, customer engagement, and ultimately, profitable growth. However, when successfully addressed, this wealth of data does deliver significant dividends. So what is the answer?
The emnos approach is to identify what absolutely must be known and what decisions we want to affect – all achieved using analysis, algorithms, and data visualization techniques which turn the data into a story and the story into a decision-support system. Today, spreadsheets have generally been replaced by investment in computing power, machine learning, data mining, visualization tools, and more. But machines cannot solve everything alone (yet!) – so a team skilled at uncovering insights is critical.
From insights to personalization
Even if they do not use the same terminology, shoppers are increasingly demanding personalization and so it has become a buzzword in driving customer engagement. The insights mined from data will provide all the necessary information to develop a more relevant, tailored offer.
There is no universal approach to personalization, some retailers and brands are at very advanced stages and others just starting out. However, the most important step will always be to lay the foundations for success, which include: knowing your customers and what motivates them; recognizing their affinities; leveraging behavioral data to better understand their actions and drivers; experimenting while in-market; and learning from your experiences. Try different approaches, build on what already works and measure the impact. Measurement is an essential mechanism to support improvement over time.
The end result - achieving engagement
Deploying the right combination of technology and human expertise will enable you to tame and intelligently mine the vast overload of available data. This produces the insights needed to build relevance and incorporate personalization into the overall brand strategy, which in turn drives greater engagement and loyalty.
With customers seeking personalization in order to engage, it is becoming even more imperative for retailers and brands to understand how to fulfil their customers’ needs. The best way to get customers to engage? Data. Data turns deep insights into a deeper understanding of behaviors, shopping patterns, and purchase likelihood. This intelligence leads to tailored content which rises above the noise to speak directly to shoppers and hence generates greater engagement and loyalty.
Data. Personalization. Engagement. The three keys to loyalty.