Today, marketers sit at the critical intersection of a business and its customers. As B2C organizations reach digital maturity, CMOs have become gatekeepers to enormous amounts of valuable customer data – like purchase history, campaign responses, social media activity and more. The CMO’s ability to transform that customer data into business impact makes her one of the executive team’s strongest contributors to company success.
But with this newfound role comes new levels of accountability for revenue growth. Once a “brand ambassador” working with agencies to build hard-to-measure marketing campaigns, CMOs today are expected to be “CEO-like” in pursuit of profitability throughout all facets of the go-to-market strategy.
Marketers who are successful in maximizing revenue recruit only the most effective tools and processes to support profitability. Marketers who aren’t successful often pursue solutions that are full on promise and low on payoff. Here are our top four mistakes in the hunt for additional campaign revenue.
1. Betting on customer segmentation
Segmentation is a powerful way to understand your customer base and support go-to-market strategies. Businesses can often make better decisions by using data-driven technology to break down high-level personas into smaller segments and provide a more detailed picture of their customer base.
But for marketers in pursuit of campaign revenue, having a segment of customers doesn’t help them understand what product or offer is appropriate for which customer. A segment for “gamers,” for example, may help a retailer understand the high-level interests of their customer base — but it doesn’t tell marketers whether a customer wants to purchase a roleplaying video game like World of Warcraft or a party video game like Mario Kart.
As a result, marketers delivering offers to “gamers” segments end up flooding customers with irrelevant offers, while also excluding many customers outside of the segments who have interest in the product. This damages profitability in two ways: It leaves campaign revenue on the table, and potentially provides poor experiences that drive valuable customers away.
For more on how customer segmentation misses revenue opportunities, check out our blog post on the topic!
2. Focusing on customer experience versus profitability
For good reason, many marketers consider customer experience (CX) a top priority. Great CX drives customer satisfaction, reduces churn and improves brand loyalty – which usually results in repeat purchases and campaign revenue lifts.
But it’s not always easy to track and measure whether investments in CX are paying off. Sales and brand experiences play out across touchpoints like email, social, display and in-store. So, while your current investments in CX may correlate with revenue upticks, how can you determine the best strategies and investments to make in 2019 and beyond to maximize campaign revenue?
According to Gartner, CMOs may never need to answer that question. The firm predicted that by 2022, CX will be replaced by profitability as the CMO’s number one strategic priority, reducing investment in marketing-funded CX programs by at least 25 percent.
Gartner attributed this to inflated investments into CX in the past several years, which are now leading to executive scrutiny as expectations in these investment areas rapidly intensify.
Instead of continuing to invest aggressively in CX alone, CMOs in pursuit of profitability are evaluating the potential for AI-driven solutions to identify signals in customer data and match campaign topics to customers most likely to purchase. This strategy can drive an average campaign revenue lift of 79% and move the needle on company revenue — all while delivering exceptional CX through highly relevant messages.
3. Rushing to adopt trending tech
According to Gartner’s “CMO Spend Survey,” in 2018 marketing technology surpassed agencies, paid media and labor as the CMO’s number one budget allocation. The message is clear: CMOs are betting big on the ability for martech solutions to increase marketing effectiveness across the board while reducing other costs.
But as an AI company, we know a thing or two about hype. And most marketers know from experience that rushing to adopt a technology because it may provide a competitive edge can ultimately damage the effectiveness of a marketing organization. The main reason for failure is the decision to invest in a trending tech without real, tested use cases that can be solved in a short timeframe and on a limited budget.
Marketers should always focus on how they can solve specific business challenges – like campaign revenue, customer engagement, in-store sales and more – and only deploy new technologies that are proven to drive results. Adding technology that doesn’t support specific goals will likely only lower profitability, sap internal resources and damage customer experience.
For more information, check out Gartner’s post, “How Much Marketing Technology is Enough?”
4. Focusing on scale versus relevance
There’s a conundrum here: To increase campaign revenue, marketers can increase campaign volume. But by increasing campaign volume, marketers end up reaching many customers who aren’t interested in the offer. Customers frustrated by irrelevant messages are likely to unsubscribe or become inactive.
So, while marketers can grind out additional campaign revenue by increasing the scale of their messaging, they hurt their revenue potential in the long run by damaging relationships with existing customers. And as every marketer knows by now, acquiring a new customer is five times as costly as retaining an existing customer.
What’s more is that consumers have had a taste of unique, tailored experiences, and their expectations for marketing communications are high. Every little bit of personalization helps: According to a 2018 report from Accenture, 91% of consumers are more likely to buy from a retailer that recognizes them and provides relevant recommendations or offers.
The bottom line from a business perspective, according to Gartner, is that digital businesses can increase their profits by up to 15% by deploying smart personalization technologies that recognize customer intent.
The most effective of these technologies are driven by deep learning, which enable marketers to drive hyper-personalized communications that resonate with individual customers. Most importantly, because these solutions become more effective with higher volumes of data, they offer a unique opportunity for CMOs to focus on revenue without sacrificing scale.