2017 Predictions for Mobile Marketing and Loyalty Trends

Mobile marketing and customer loyalty are not new ideas or tactics, but the strategy behind them has been evolving dramatically in the past few years, and that momentum is going to continue through 2017.

According to eMarketer, the majority of U.S. marketers intend to allocate more of their budgets to customer loyalty in 2017, and about 13 percent said they anticipate significant increases in spending on such programs.

For brands and marketers, their strategy needs to go beyond just having an application or a stagnant loyalty program. There are a multitude of mobile channels, methods of communication and personalization capabilities that can be leveraged to really engage consumers through their mobile devices. Here are some predictions to help curate mobile marketing strategies heading into the new year.

Toss out the legacy marketing stack and take a look at single-view technology

The old days of mass campaign emails pushed out through legacy marketing stacks are behind us now. According to McKinsey & Co., 83 percent of marketers identify that the ability to make data-guided decisions is one of the most important capabilities, but only 10 percent believe they are effective at feeding insights about customer behaviors back into the organization to improve performance.

Measuring campaign success on whether or not an email was opened won’t cut it anymore. Companies need to have a single view of online and offline systems across multiple channels so that they can build single, operational profiles for each customer.

2017 will pave the path for becoming more agile and making data real-time and actionable in the mobile-first world. Behavioral and transactional data and syncing individual profiles will be the only way to reach customers, not through campaigns built for large masses. Companies need to make sure to integrate their technologies to make their once siloed marketing stack more agile, real-time and actionable.

It’s not just for the movies anymore … machine learning is for mobile marketing, too

Machine learning is rapidly infiltrating almost every industry today, and mobile marketing is no different–especially when it comes to the real-time needs for marketers. By leveraging advanced analytics tools, machine learning helps brands gather predictive data, detect patterns within massive databases and thereby power predictive responses for personalized marketing automation.

For example, brands could use machine learning capabilities to understand customer product preferences based on historical purchases. From there, when a customer enters the store the next time, it can allow the brand to send a push notification at that specific moment with a relevant offer–allowing for a hyper-personalized customer journey.

Omnichannel experiences

According to DMNews, 53 percent of consumers feel that it’s important for retailers to recognize them as the same person across all channels and devices used to shop, and 78 percent are also willing to allow retailers to use information from their in-store purchases to provide a more personalized experience.

Brands and marketers need to start giving consumers that they want—omnichannel, personal experiences.

Hearing it straight from the consumer’s mouth, 2017 will be a year for customers to be treated as individuals, with a consistent brand experience regardless of what channel they’re using. By creating a single view of the customer, brands can ensure that they are not only following the journey across all platforms and channels, but also reacting to it at the points of highest value.

A good example of this is if a store sees that a customer has left items in an online shopping cart. Rather than sending an email reminder in a few days about the forgotten items, a brand could, and should, instead send a push notification as the customer enters the store to remind them of the items.

It’s not just about likes … brands need to see the bigger picture through social media

It’s hard to remember the days when social media did not exist in our lives–it has become essential to everyday life for both consumers and brands.

Despite the pervasiveness of social media, though, DMA recently reported that 70 percent of companies are still not collecting data from social media channels. And I don’t mean counting likes, follows and favorites, but the actual data in the content of those social media posts.

Brands looking to strictly advertise to and convert customers on social media are missing a huge opportunity to unearth a plethora of data about consumer trends, purchase intent, product attributes, drivers of sentiment, competitors or category-level conversations.

By analyzing the social conversation across platforms, brands can respond in real-time with hyper-relevant content. For example, if there’s a spike in conversation about unseasonably warm weather in the area, a coffee chain could push a local campaign offering discounted iced beverages for the day.

Getting personal with your customers

Acquiring new customers is important, but retaining your best customers is critical. According to Forbes Insights/Sailthru, companies that increased their spend on retention in the past one to three years had a nearly 200 percent higher likelihood of increasing their market share in the past year compared with those spending more on acquisition.

Traditional loyalty programs rewarded existing or passive behaviors to try and reduce attrition, but the actual rewards are typically generic and generalized and not tied to specific milestones, behaviors or thresholds.

Moving forward, in order to have a successful omnichannel and mobile loyalty strategy, marketers need to align cross-team stakeholders to define business goals and identify what their high-value customer behaviors actually are.

With key milestones and behavior change thresholds defined, programs can offer specific rewards to customers to motivate long-term loyalty and deepen engagement. Brands and marketers can also use their data to quantitatively determine which customers are the best ones by looking at recency, frequency and spend metrics, and targeting accordingly. Each customer should have their own unique experience with individualized incentives.

Brands and marketers can no longer just check mobile off of their to-do list for their 2017 budgets. How are you leveraging mobile? Do you have an omnichannel approach? Is it personalized? Are you looking beyond your likes and reading actual customer conversations on social media? Mobile marketing is set to be a dominant marketing force over the next year; how’s your strategy looking?

Rachel Newton is the marketing director at loyalty marketing technology provider SessionM.

Image courtesy of Shutterstock.

Source

Fun with robots.txt

Columnist Patrick Stox provides some dos and don’ts for creating your robots.txt file — along with examples of companies who have gotten creative with their files.
The post Fun with robots.txt appeared first on Search Engine Land.

Please visit Search Engine Land for the full article.

Source

Top Four People-Based Marketing Use Cases

A few weeks ago, I flew to Houston, Texas. It was great–a short, comfortable flight. And, there were enough vacant seats to give our youngest her own. After an hour, I picked up the shopping magazine in the pouch in front of me, despite having never bought anything throughout decades of flying. I couldn’t help it.

After flipping through page after page of seemingly useful — yet, unconventional — products, I came to the same conclusion that I’ve come to for years: Not one product had a valuable use case for me. All of them were solving problems I didn’t have.

As marketers, we sometimes slip into this trap of spamming our consumers with products that solve problems they don’t have. Oftentimes, it’s not that we don’t have the right product, but rather, we don’t have the right context. A single-device understanding of consumers doesn’t provide enough context to deliver truly personalized offers, especially considering that the average consumer owns more than three devices.

People-based marketing solves this problem. People-based marketing means that you don’t treat a device as a person. Instead, you can link devices that are used by the same person and then treat that person as an individual across all their devices.

Top Four People-Based Marketing Use Cases
With the correct components in place, people-based marketing can have a major impact on everything marketing — from reporting and analysis to attribution and experience. In this post, we’ll walk through the top four use cases for people-based marketing.

1. People-Centric Reporting and Analysis
Historically, digital-marketing measurement was built on a foundation that was intended to understand people but designed to understand devices. When a device graph is integrated with an advanced analytics solution, the device graph can transform the context of reports from being device-centric to being people-centric. This means that — for the first time — marketers can understand how many people (rather than phones and tablets) visited their site, or how many people (rather than laptops and Apple watches) interacted with their brand across multiple domains, apps, or even a brand’s offsite advertising.

internal-image-1-top-four-people-based-marketing-use-casesTo illustrate this point, let’s imagine a marketer launches two campaigns. The first campaign reports $10 of revenue per visitor. The second campaign reports $20 of revenue per visitor.

Using a device-centric metric (like revenue per visitor) creates the impression that the second campaign, costs being equal, is more effective. However, using a people-centric metric to analyze these campaigns, the same marketer might see that the first campaign touched one person across three devices, making the revenue per person $30; compared to the second campaign that touched one person on one device, giving the campaign a $10-per-person revenue. From this insight, an analyst could build a compelling case for promoting the first campaign to hit their quarterly revenue target.

People-based marketing gives marketers insights on people — not devices.

2. Seamless Cross-Device Experiences
Personalization tools strive to deliver meaningful experiences, but these tools alone can only deliver the right experiences to familiar devices. What happens with unfamiliar devices your customers use to interact with your brand? What do they see then?

For example, if an avid reader made it halfway through a riveting article on her tablet, and then visited the same website from her phone to finish reading the article, what kind of experience would she have? She’d likely fumble over the keys to enter a search, scroll down the page, and meticulously comb through each line of copy until she found exactly where she left off — far from ideal.

A people-enabled personalization tool offers a drastically different story. The reader would get halfway through the article on one device, pick up another device that she has never visited the publisher’s website from, and still be brought to the exact article she was reading on the first device.

People-based marketing makes seamless, cross-device experiences possible — experiences that are continuous, consistent, and compelling.

3. Cross-Device Efficiency for Advertising
Traditional advertising platforms, just like analytics and personalization platforms, are susceptible to the same device-centric limitations.

For the display advertiser, keeping tabs on his ROI is a relentless top priority. A common way to assure the return on ad spend (RoAS) is maximized is to apply a frequency cap on the number of times someone sees the same ad. Unfortunately, frequency caps apply to devices — not people. So, a frequency cap of five impressions per person can quickly become 20 impressions per person if each person uses an average of four devices. This leads to wasted ad dollars and perturbed customers.

People-enabled advertising platforms apply frequency caps that span the various devices used by a person. A cap of five impressions means a cap of five impressions for a person. Using the previous example, a people-enabled advertising platform could have delivered a 75-percent higher ROI than the non-people-enabled advertising platform.

4. Holistic Attribution
Attribution is constantly evolving to include more touchpoints, more-accurate weighting, and machine learning. So, it’s ironic that one of the most important factors in understanding the impact of marketing on the buying behaviors of people has always been missing.

Traditional attribution algorithms only analyze pre-login information from a single device. And, considering that the average person owns three devices, it’s likely that a big part of the attribution story is missing.

For instance, if a consumer visited company A’s website from her laptop, was retargeted with a display ad, and then finally converted on the website; a linear-attribution model would yield something like this:

internal-image-top-four-people-based-marketing-use-casesBut, in reality, this same consumer also conducted a search on her phone, read an article from company A’s site, and then went back to her laptop to make the purchase. Using the same linear-attribution model that’s being fed information from a device graph would yield this:

internal-image-3-top-four-people-based-marketing-use-cases

After a month, the marketer sees that this same article is among the top-ten, most-valuable traffic sources according to the linear-attribution model. As a result, the marketing team surfaces the article’s dialogue on all product pages (which truncates the customer journey to three touches), decreases their search spend on the keywords that point to the article, and all-in-all delivers a better experience to consumers as well as a stronger bottom line for the business.

With holistic attribution, marketers can now prove the value of all their marketing within the context of people — not devices.

A Very Real Payoff
Marketing has always been about understanding consumers to the extent that our messages and offers deliver solutions for which they are willing to pay. But, it’s only recently that nailing these key ingredients alone won’t necessarily convince consumers to make purchases. Consumers want consistent, continuous, and compelling brand experiences. Device-centric marketing can’t deliver this — but people-based marketing can!

While I haven’t personally purchased anything from in-flight magazines (like SkyMall), they’re successful business endeavors, and their magazines have been my go-to source for in-flight entertainment for many years. With a captive audience of people looking for a distraction while their devices are stowed, SkyMall may not need people-based marketing. For the rest of us, people-based marketing is like setting your tray table and seat in the upright position — you simply have to do it.

The post Top Four People-Based Marketing Use Cases appeared first on Digital Marketing Blog by Adobe.

Source