Partner Voices: Turning Analytics Into Profits

In the third and final installment of this three-part series on data analytics, we get to the heart of the matter: How can digital intelligence translate to an improved bottom line? Because at the end of the day, that’s what all retailers are after. (Here are parts one and two in case you missed them.)

Today’s e-commerce landscape can aptly be described as a battlefield, with thousands of retailers (including one very big one that calls Seattle home) fighting for consumers’ wallets. So what decides who wins … and who loses? Experiences. The brands that are able to give consumers the exceptional experience they demand will win their business, and the brands that can’t won’t be around for very long. That’s the harsh reality.

Therefore, what does it take to provide consumers those exceptional experiences that will keep them coming back time and again? Knowing who they are and what they like. That’s where analytics comes into play. Having the right customer analytics strategy is essential to achieving your goal — running a profitable business.

Knowledge Drives Loyalty
Gaining deeper insights into your customers leads to happier, longer-term and more profitable relationships with them. This isn’t merely conjecture; it’s supported by data. According to a recent survey by Econsultancy and IBM, Secrets of Elite Analytics Practices, 30 percent of the respondents with strong customer journey analysis enjoy conversion rates 104 percent higher than those with less sophisticated capabilities.

The benefits of having a complete understanding of your customers’ journeys aren’t limited to conversion rate, however. Customer satisfaction and revenue growth are two additional byproducts of a strong analytics program. Case in point: those same 30 percent of respondents with strong customer journey analysis receive customer satisfaction rates that are 27 percent higher than the rest of the sample, as measured by Net Promoter Score.

Furthermore, the Econsultancy/IBM webinar cited an example where customer analytics maturity was used as a baseline to divide respondent companies into elite, average and laggard groups. Elites were defined as those organizations with strong capabilities in customer journey and struggle analysis as well as insight automation. The companies within the elite group enjoyed a revenue growth rate 19 percent higher than the rest of the sample.

The Value in Easing Consumers’ Struggles
Most retailers have traditionally used analytics programs as tools to better understand customer behavior and evaluate and improve customer experiences — and wisely so. Yet if they limit the use of analytics for only those two areas, they’re missing an opportunity. The elite organizations in the report were significantly more likely than the average and laggard companies to cite “understanding where and why problems arise” — i.e., customer struggle — as a primary benefit of their ability to gain customer knowledge.

I go back to an example from part two of this series: knowing that site visitors are dropping off at the checkout page is useful information; knowing why they’re doing so is game-changing information. For example, if you see that when shipping costs are added to a customer’s order total on the checkout page it’s making them more likely to abandon their cart, you can take action on this information by including the shipping costs on the product detail page, thus avoiding any surprises when shoppers get to checkout. The data lead to an action, which lead to more conversions which, ultimately, lead to a healthier bottom line.

Sharing is Caring
Gathering, analyzing and using digital intelligence to improve the customer experience has traditionally been a task delegated to the marketing/digital team. The problem is that for most retailers, that’s where it ends. The data isn’t shared across the organization.

This is despite the fact that digital intelligence, whether it’s customer, competitor, industry, product, etc., is extremely valuable across a retailer’s organization — not just the marketing department. Those brands that are sharing data across their organizations are at a distinct advantage over those that are not.

According to the Econsultancy/IBM report, 81 percent of companies with elite analytics practices describe information sharing between teams at their organizations as highly successful. Compare that with 59 percent of laggards that admit their organizations are unsuccessful at sharing information between teams. The value in sharing data — i.e., making it accessible to all teams via a single dashboard — is clearly evident.

So why aren’t more retailers proactively sharing digital intelligence across their organizations? For most, it comes down to a lack of capability within their current analytics platform and/or a lack of trust in the people accessing the data. Don’t let these challenges stand in your way of a better understanding of your customers by all within your organization. The end result — more loyal customers, who have a higher lifetime value — is well worth it.