Ever taken a long and hard look at the content on your website? If visitors are bouncing and customers aren’t opening their wallets, you may have a problem. By gathering data from visitors and customers’ actions, you can design and deliver a better experience for them.
A successful entrepreneur is one who knows how to use data insights to make better business decisions. One such decision would be to determine what kind of content strategy would generate more leads and facilitate more sales.
But you can’t make a well-informed decision or craft a strategy unless you democratize data. Your sales reps and marketers may have more “on the ground” knowledge than your boardroom directors. You need to gather this knowledge, build on top of it, and use it to make your sales and marketing processes more effective.
Here are some success stories of companies that use insights cleverly.
Dove
Dove is considered a pioneer when it comes to leveraging data. It was one of the first beauty brands to undertake research on a global scale and use key findings to create a meaningful ad campaign.
Dove’s research on “The Real Truth About Beauty” (first commissioned in 2004 and then revisited in 2010 and 2015) highlighted a universal problem related to beauty and body image. They found that barely 4 percent of women around the world consider themselves beautiful.
This led Dove to fundamentally change their vision as a brand. They went on to partner with many health and beauty experts to develop impactful materials and deliver them to their target audience (young women worried about body image) in various content forms.
Dove’s research-based campaigns have been analyzed, praised and cited hundreds of times by marketers and academics alike, partly because it is hugely successful and partly because it is an altruistic and sanguine way of promoting and selling products.
It isn’t difficult to see, however, that the real hero of the campaign is big data analytics, without which it would have been impossible for Dove to discover “the real truth.”
Lenovo
In June 2015, computer manufacturer Lenovo started using a text analysis tool to track and act on data from product surveys, product feedback and support chats, as well as monitor conversations and audience opinions on online forums and social media.
The direct result, as Daniel Bieber, Global Analytics Architect, revealed, was that business, sales and customer care teams stopped having the same conversations over and over again, and executives no longer had to make decisions based on their gut feeling.
Lenovo was able to identify and tackle specific problems before they turned disastrous. For instance, they found that the most pressing concern their laptop customers had was battery life. While the product department took remedial steps, Lenovo also developed new content that talked about maximizing and extending the battery life of their entire range of products.
Sometimes data generated by big data tools amount only to noise. It is very difficult to narrow in on the problem and solve it. When Bieber and his team used text analysis, they found many common themes and recurring trends. This helped them to act quickly and create content that effectively addressed customer pain points.
Spotify
Warc recently reported that Jeff Rossi, Global Director of Business Marketing at Spotify, believes brands should stop making assumptions about their customers and target audience, and instead focus on consumer behavior insights for more effective targeting.
According to Rossi, data collected by music streaming offers 15 times more data points than other media sources. These might not include typical ones such as demographic, gender or location, but music reveals moods and mindsets better than any other data source, he claims. Data on listening habits could be the missing link that unlocks deeper insights on buying intent, moods and motivation for brands.
Traditional segmentations don’t allow brands to match their content to a certain time of the day, habit, mood or activity, but Spotify opens up these possibilities. For instance, there is a playlist called the “shower playlist” on Spotify with more than 500,000 listeners every morning! Can you imagine what a shower gel brand would give for an ad spot there?
Smart entrepreneurs must go beyond age group, location and gender to see the possibilities beyond the usual. Just as there is a Shower playlist, there is a Monday playlist, ideal for coffee brands and a Roadtrip playlist, which provides a perfect milieu for travel portals. This is contextual strategizing at its best.
Developing in-house capabilities to follow the leaders
While Dove and Lenovo used insights from customer behavior to craft content strategies for their own brand, Spotify showed brands how to use data from media platforms in unique ways.
If you want to model your content strategy on those of top brands, here’s how you can develop the right capabilities in-house:
Educate yourself
One of the most desirable traits of entrepreneurs is the ability to focus on big picture. This ability can be acquired with the help of big data tools and the knowledge of content, user behavior and marketing trends. If you have big data tools but lack the knowledge of leveraging data insights to devise marketing strategies for your content channels, you may find it difficult to survive in today’s data-driven world.
New age entrepreneurs and startup founders, who don’t usually have an academic business background, can acquire this tactical know-how with the help of a business management course. A sound business course can help you cultivate technical skills that are harder (and counter-intuitive) to learn on your own.
Emulate the success stories
While every business is unique, some lessons can be replicated to suit your own business. You can also use news and sentiment analysis data to create content of your own.
For instance, there is no dearth of news on the tense geopolitical situation in eastern Ukraine, but only Capital Market Exchange, a Boston-based firm, uses this data to evaluate risks for their clients and create visual data, contextual comments and other forms of content that helps organizations affected by the situation make informed decisions.
Experiment and adjust
Relying on insights alone might be catastrophic – you always run the risk of collecting contaminated data or inferring the wrong thing. To avoid making damaging decisions, keep watching your metrics and vetting your tactics.
The most common form of measuring the impact of changes to your website or app on your bottom line is A/B testing or split testing, which involves comparing two different variants (with differing elements) of the same page/screen to see which version gets you more conversions. This takes the guesswork out of your marketing campaigns and UX optimization efforts.
While the concept is simple, you might get inaccurate results if you aren’t careful with assumptions, execution methods and conclusions. A/B/n testing with multi armed bandit techniques is often effective in present-day content strategies.
Over to you
Businesses today have easy access to customer data. But collecting this data and using it to improve business processes is easier said than done. From real world examples to actionable steps, now you know everything about creating content strategies based on data insights. By 2020, big data will be beyond big; it will be the be-all and end-all of content marketing. If you are not using big data wisely, you might find yourself overtaken by leaner, more progressive competitors with bigger ears (who listen to their customers)!
Data isn’t just helpful in reaching customers. Research will help you build better relationship with the media as well. Learn how to craft content with the media’s needs in mind by downloading Cision’s guide How to Make Sure the Media Gets Your Story Straight.
