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Got low site traffic? If you’re an inbound marketer, you know that investing in expensive tools and technology won’t solve that problem for you — you need to consistently create content to do that. But if you’re just creating content and lack the right tools and technology to back up your efforts, you’ll soon find you’ve hit a traffic wall. In this post, we’ll highlight the importance of having the right tools to improve website traffic.
Setting the stage: Identifying your traffic problem
Let’s say you already have a robust analytics package in place. You take a look at your funnel, and your problem becomes abundantly clear: you don’t get much traffic to the top of your funnel. Just take a look at your numbers.
So a decent chunk of the people who visit your site convert to leads — even better, 75% of people who become leads on your site end up converting to customers. Your problem isn’t converting visitors to leads, and it’s not converting leads to customers. Your problem, as you can see in the table above, is simply getting people to your website.
So what do you need to do to attract visitors to your website? In the traditional playbook, the answer was simple – buy traffic. Today, the smartest marketers are focusing on search engine optimization, blogging, and social media. In fact, HubSpot’s “2018 State of Inbound Marketing Report” showed that SEO, blogging, and social media were most frequently cited by marketers as channels with a below-average cost-per-lead, and channels that were growing in importance. So it makes sense that marketers might want to invest in some technology to make their efforts with these channels even more effective. Hey, if your CPL is below average you have some change left over. So how do you ensure that change isn’t wasted? Here’s what to look for when you start shopping.
What to look for in SEO technology
Search engine optimization is no longer the sexiest new online marketing technique (social media stole that honor some time ago), but it’s still critical to generating site traffic.
There are two basic pieces of search engine optimization — on and off the page. On-page tactics focus on the code you can actually change on a page. The good news is that on-page SEO is easy to control, the bad news is that it’s not critically important. Off-page SEO, on the other hand, revolves around the links that go into your site. Ready for some more good news-bad news? The good news is that off-page SEO is super important. The bad news is that it’s harder to control. But a marketer looking to generate more site traffic needs to be concerned with both, and understand these three main factors when evaluating technology that will help them pursue better on- and off-page SEO.
1. Keyword analysis
Keyword analysis should be the first step in any SEO process. It helps you understand which keywords you’re ranking for now, and which keywords you should try to improve your rank for. To get this kind of insight, you need to be able to generate a report of all your keywords and compare them by traffic, difficulty, and current rank. Those factors should dictate what keywords you need to focus on.
You don’t want to waste your time trying to rank for keywords for which you’re not currently ranking, that are highly contested, and that generate relatively low traffic levels. Instead, you want to focus on keywords that you’re already ranking for but could have a higher rank, that generate large volumes of traffic, and that isn’t very competitive. A good keyword tool will help you find these keywords.
2. Website tools designed for SEO
Keyword analysis tools help you develop metrics and plans for SEO, the right website tools will help you actually implement your SEO plan. When picking website tools, make sure that it’s easy to change page attributes like the title, the meta description, and the keywords, and that new pages are created with default optimization like keywords in the URL address, and automatic sitemap generation. These are all on-page SEO elements you can fully control and optimize.
3. Page-level SEO analysis
The final key piece of SEO technology is page-level analytics. You need to be able to assess the SEO quality (and inbound links) of each of the pages on your website. Ideally, you’ll be able to get a report on each of your pages, listing inbound links, their authority, as well as keywords the pages rank for, and any SEO errors on the page.
What to look for in blogging software
SEO is a critical part of building traffic to your website, but it shouldn’t be your only strategy. SEO tactics need to be coupled with content — ideally, blog content! Think of it this way, blogging is kind of like playing the lottery; would you rather have a fixed level of opportunities to rank well for a given term, or hundreds of thousands? Every time you write a new blog post, you’re giving yourself another opportunity to win the SEO lotto. So if you’re blogging to improve your SEO, and by extension your site traffic, here’s what you should look for in a piece of technology to help supercharge your efforts.
1. Ease of use
You need to be comfortable using your blogging software multiple times a week. Writing is hard enough, so you don’t need to make matters worse with difficult software. Make sure it’s easy to create, edit, schedule, and publish a post. Managing comments should also be simple.
2. Built-in SEO tools
Business blogs should be designed with SEO in mind. The post URLs should have a good SEO structure and page-level SEO features. You should have an easy way to add or change keywords for specific posts. Ideally, you’ll also be able to get SEO feedback like keyword suggestions as you write.
3. Social sharing and email subscription
Social sharing capability is a critical — and a fairly standard — component of any blogging platform. Most blogging platforms make it easy to share your posts through social media. In addition to social media following, make sure your readers can subscribe to your blog by email too.
What to look for in social media tools
Blogging and SEO are absolutely critical to driving traffic to your website, but they often struggle without a third element which is social media. For consistent traffic growth, businesses need to continue building a community of fans and followers on social networks with whom they can share their optimized content and attract new site visitors. So it only makes sense that if you’re investing in SEO and blogging software to improve your site traffic, you’ll want some social media software to help you out too. Here’s what any social media software should have to help solve your traffic problem.
1. Social media monitoring
The first rule of social media software is don’t talk about social media software. Just kidding, the first rule is actually, “listening”. Many marketers do this for Facebook, then they hop over to LinkedIn, then they move over to Twitter, and before long they have five tabs open in their browser and spend the whole day hitting refresh. In other words, platform-hopping is complicated and time-consuming. Ideally, your social media software allows you to monitor most social media discussions within one single application.
2. Integrated, multi-channel publishing
Chances are your customers and prospects are clustered across different social media sites. So if you want to reach all your customers and prospects, you need to publish to Facebook, Twitter, LinkedIn, and any other sites where your audience hangs out. It’s a lot of work to publish a single piece of content on multiple sites, so you should make sure your social media publishing tools allow you to publish to all of them at once.
3. Easy social media following
Building a following is a critical part of social media. The bigger and more engaged your network, the greater your ability to use social media to generate traffic for your site. You should have an easy way to encourage your community to follow you on your website, on your blog, in your emails, and in other places that you generate lots of new traffic.
4. Reach tracking
Reach is a key metric for marketing teams. It’s an indication of your ability to generate attention and traffic. A great piece of content will have a much bigger impact if it’s driven by great reach. Your social media tools should make it easy to track the aggregate reach of your social media channels.
A note on the importance of integration
All of these components are critical to a great piece of SEO, blogging, or social media software but integration with one another — and your other marketing technology, as well — save marketers’ time, money, and a whole lot of grief.
Let’s take your SEO tools, for example. Wouldn’t it be nice if your page-level SEO tools were integrated with your website management software? It would be a whole lot easier to fix errors that the report turns up if that were the case. Similarly, if your SEO tools are integrated with your marketing analytics tools, you can see the leads and customers generated from the keywords you’re targeting. Same for your blogging tool — if it’s integrated with your marketing analytics tool, you can track the blog posts that drove the most leads and customers. And your social media publishing tools should be operating right alongside your website, blog, and landing page tools. Just think how much easier your life would be if you could track the social media activity of contacts in your marketing database, and track the leads and customers generated by social media.
The point is, you can do all of these things separately, but time is rarely an excess resource within a marketing department. If all of your tools and technologies are integrated with one another, you spend less time compiling data and reports, and more time analyzing and improving upon your marketing activities.
Want to learn what other marketing problems the right technology can help you solve? Leave a comment.
Corey Wainwright is a Bruce Springsteen fan who does content marketing, in that order. She is Director of Content at HubSpot.
Good data is the lifeblood of effective marketing. Not only is it hard to obtain good data, but once we get it, we are often overwhelmed by the volume and the number of things that we can do with it. Calls with customers are one of the richest sources of insight that we’ll get, yet this data is very rarely used effectively.
We’ll examine three call data strategies that every marketer should be aware of, to inspire you to get started. Then watch the full masterclasses with call-data expert, Blair Symes to learn how to make the most of call data in your organization.
Marketing starts with understanding customers. As marketers our job is to gather every data point we can, to understand who our customers are and then clearly communicate these insights with the rest of our business. Marketing makes the customers real, bringing their needs and desires to live and helping businesses more effectively serve them.
Content produced in collaboration with DialogTech.
Finding valuable insights in our customer data
Historically, we’d get our insights from quantitative surveys and qualitative focus groups, often analyzed and interpreted by research companies. But in the digital age, modern marketers must continually search for further sources of customer data, particularly as consumers embrace new technologies and as new measurement and analytics tools emerge. There is now more data available than ever before. We can be overwhelmed with the volume of data and insights that we can already glean from social media and Google analytics. The challenge now has become, how do we find the signal in the noise?
Segmentation is a useful exercise to group customers by shared interests, profiles or needs. When we have enough data, we can start to identify patterns and natural groupings, we can start to build personas, or archetypal individuals who represent each segment such as ‘Soccer Mom Susan’, or ‘Consultant Kate’. Once we have these personas, we can introduce them to the rest of the company. When the whole of the company knows who Gary and Susan are, it becomes a whole lot easier to explain marketing campaigns, and of course to then get them implemented successfully.
We should be constantly evolving our personas, because our customers are constantly evolving. We should be looking for any other insights that will help understand how they are changing. But rather than passively researching, we should be actively generating and testing hypotheses about our personas that we can validate with real data.
The best consumer insights I’ve ever had have come from listening to actual conversations on customer calls.
Every marketer should listen in on calls, as regularly as possible. The more senior you are, the more important it is to listen in and stay connected to your customers.
But what do you do with these insights? They are valuable, but their value immediately depreciates if you don’t action those insights. At a minimum we should be tabulating these insights and updating our personas, but you start to get real value when you can add these insights into your CRM and marketing automation tools and start to adjust your marketing campaigns based on these insights.
Diligent marketers spend time capturing these insights and adding them to their CRM, but the challenge then becomes how do we scale this process when the volume of data increases? As businesses grow, so do the number of customer calls, both sales calls and customer service and it becomes too time consuming to listen in to each and every call. Marketing teams become overwhelmed. This source of consumer insight ‘gold dust’ is left unsifted.
Over the last couple of months, I’ve been exploring exactly this challenge with Blair Symes from DialogTech.
You can watch the two webinars we’ve done that explain more:
Here are three strategies for using call data to make your marketing more effective
Watch the full webinars for more insight and case studies on each.
1. Reduce cost per acquisition (CPA)
An increasing number of customers are calling directly from mobile, after clicking on a search ad. This gives you the opportunity to gather a tonne of useful information, particularly what message resonated best and what finally convinced them to buy from you. As you start to build up data about successful conversions to sale, you should start to see some patterns emerge that you can use to identify which campaigns/ messages are most effective. At the same time, you can also look at the ads that were effective at driving calls, but that didn’t convert.
Being able to see the journey from ad, to call to conversion, allows you to identify the best performing ads, to refine and to optimize spend.
2. Change the language we use when talking to customers
Language can make all the difference to sales conversion. From the message used in the original ad, to the landing page, and the script your sales teams use, language has the power to significantly affect your ROI. The good news is that by listening in to your customer calls, you can start to record the language that you customers are using. This can then inform the language you use in your ads, landing pages, IVR and sales scripts.
The most powerful example is from handling objections: Listen to the language the customer uses when they’re talking through their concerns (objections) prior to converting. Then use that language earlier in your sales script to pro-actively manage their concerns, or add a new video, whitepaper or FAQ on your landing page specifically about those particular concerns.
Understanding and reflecting the language that customers use, helps make all of your communication more effective, more natural sounding for your customers and inspires the production of useful and relevant content.
3. Identify audience segments and activate externally
Developing audience personas not only brings our customers to life, but it helps us group them and prepare specific messages and campaigns based around a common need or interest. Our calls are full of information that we should collect to build up detailed profiles, for example: demographics, income, marital/ family/ work status, geographic location, interests. It could also be that we know if they’ve bought from us in the past, or maybe they’re browsing but haven’t purchase yet.
Once we’ve built up these audience segments, we can target and re-target them with messages that are relevant or highly targeted offers and promotions based on what we know they’re interested in. This targeting can be done through social advertising and paid search, as well as being activated through display platforms. When you start to see results, then you may want to look at building ‘look a like’ audiences to extend the reach of your campaign.
By understanding more about our customer segments, we can create highly targeted campaigns with significantly improved performance.
The problem of volume in customer calls
Those are just a few examples,that Blair explains in more detail in the webinars. You can see that there is a lot of potential to capture data and generate insight from your calls, but the problem of volume persists: How can we listen in on thousands of calls and extract anything meaningful. Luckily, that’s where machine learning comes to the rescue.
DialogTech was developed specifically to help record all your incoming calls, and then to process those calls using AI, to extract meaning. It’s a perfect example of AI helping marketers with the challenge of finding a signal in the noise. Once you’ve identified some patterns, or profiles, then DialogTech integrates with your activation platform (such as Facebook or Kenshoo) so that you can put those insights to use straight away and start to increase the performance of your campaigns.
Watch the webinars to learn more about this fascinating subject and hear how DialogTech are using AI to help marketers make the most of their call data.
Tel Aviv-based TechSee has unveiled what it says is the first AI-powered visual recognition for contact centers.
Called TechSee Smart, it builds on the company’s success with its previous TechSee Live. With that earlier service, contact center agents can see still images or video on a customer’s smartphone and make drawings for the customer on top of the visuals in an augmented reality layer. The firm says more than 100 client companies are currently using TechSee Live.
Analyzing the problem
Image from TechSee
The new service allows a smartphone-calling customer to send still images or video to the contact center, which are then processed by the TechSee Smart platform to determine the product model and the cause of the problem.
In a typical use case, the contact center’s interactive voice response (IVR) system sends a SMS link to the customer’s smartphone, while the customer is speaking with a live agent or while waiting for one.
Through the link, the customer sends several photos or video clips of the product having a problem. The TechSee Smart platform, which is integrated with Salesforce’s customer relationship management (CRM) system and several contact center platforms, visually analyzes the imagery, recognizes the product and determines the likely problem — assuming there are visual indications.
Chatbots can’t tell what’s wrong
For example, the platform could let the agent know that the product is model #ABC cable set-top box, and that one of the connecting wires is attached to the wrong connection. The TechSee Smart platform’s deep learning technology is trained with images and data relating to actual use cases in contact centers, primarily in the industries of telecommunications, consumer electronics and utilities.
VP of Product Marketing Liad Churchill told ClickZ that the processing of objects and the likely cause of the problem should take only a few seconds, once the images or video clips have been uploaded. He added that his company’s testing indicates TechSee Smart’s issue resolution is about 95% accurate.
The primary use case for TechSee Smart is when a user calls on the smartphone, and Churchill said about 90% of users calling into contact centers do own such a device. If the user communicates through a landline phone or a computer, the agent can also send a SMS link to the user’s smartphone.
Churchill added that, today, spending in customer service for AI is largely for text or data analysis, but “chatbots can’t tell you why your [product] isn’t working.”
Now we’ve reached those two years, and most marketers understand that data-driven, personalized communication with customers across devices is indeed a dealmaker or dealbreaker for many of today’s consumers.
However, understanding that personalization strategy is a priority, and successfully personalizing each interaction with customers are two very different things.
In fact, a 2019 customer experience trends survey found that two-thirds of customers could not recall when a brand last exceeded their expectations. Yet, that same survey found that 87% of marketers think they are delivering engaging customer experiences. Clearly, there’s a disconnect when it comes to marketing’s ability to deliver what consumers expect.
What will it take to close this gap in customer experience?
There are signs of progress — Gartner’s CMO Spend Survey 2018-19 found that customer experience initiatives would be allocated 18% of overall marketing budgets (compared to 21% on advertising) — but still, consumers’ lofty expectations are quite hard to match. And no matter how much budget marketing throws at the problem, that doesn’t necessarily equate to consumers’ perceiving improvement.
Most marketers are dealing with vast and disparate sets of data, legacy platforms, and numerous point solutions. And more technology hasn’t always meant more answers. Rather, 74% of marketers feel that technology has made it harder, not easier, to deliver personalized experiences.
Many businesses launch personalization efforts without having a full, data-based picture of who their buyers are — and then they don’t understand why their personalization efforts aren’t getting results. Often, the problem for marketers lies in lack of strategy: knowing where and how to start, and growing from there.
Personalization strategy into a three part crawl-walk-run approach1. Learning to crawl
Getting started with customer data means beginning to build a complete and accurate view of exactly who your customers are — a feat that most marketers are still struggling with. A study by VB Insights found that 80% of marketers don’t understand customers beyond basic data. And nearly all of those surveyed (96%) said they faced challenges when building a single view of a customer.
These challenges could be the result of the fact that many businesses are trying to walk (or run) before they can crawl when it comes to data and personalization.
Learning to “crawl” means starting with some basic data and generating small, personalized interactions using that data. Understanding characteristics like geolocation, device type, operating system, and new versus returning visitors are critical components to building a 360-degree customer profile.
Some examples of crawl personalization include understanding which pieces of content perform better on mobile, offering up location-based homepages, and generating personalized homepages for users who click through from an email.
At the crawl stage of personalization, it’s also important to start thinking about which martech tools can best help your company gain a 360-degree view of your customer. There are thousands of martech tools on the market, so knowing exactly which information you’re trying to gain about your customers is essential for helping choose the right tool for your business.
2. Starting to walk
All too often, we’re collecting data hoping to solve very specific problems. There’s nothing wrong with wanting more clicks and page views or better leads. But collecting customer data with an eye towards personalization should be about discovering what the data can teach us, rather than how we can manipulate the data as a means to very specific ends.
Instead, allow the data you are collecting, profiles you are building, and segments you are creating to teach you things about your visitors and your business.
Companies entering the “walk” phase of personalization are starting to use their data not just to build a complete picture of their customers, but to start creating experiences based on the lessons that data has taught. For example, a fashion brand may use location-based personalization to showcase coats to buyers in New Jersey while still promoting bathing suits in California.
Personalization could also mean delivering newsletter sign up promotion to a first-time visitor to capture their email or directing them to download an app for a different user experience. The walk stage is all about segmenting your user base into much more specific groups which you can continually target and test content against.
3. Running with it
As your business transitions from the “walk” to “run” stages of personalization, you’ll probably have an inherent understanding and visibility into your audience’s implicit preferences like content, experiences and so on, resulting in a completed action. Keep in mind that your goal is to use your technology to not only move your customers along the funnel, but also to deliver great experiences every step of the way.
Businesses that are ready to run in terms of personalization have used their data to segment audiences and copiously test content so that they have a complete picture of the buyer journey from awareness and consideration to conversion, growth, and advocacy. At each of these touchpoints, both online and offline, brands have an opportunity to reach customers with data-driven, personalized experiences that increase their engagement and their loyalty.
Businesses that are running with their data and personalization have unified their martech and adtech touchpoints, consolidated customer data for one-to-one or one-to-few engagement, and are using those tools to automatically trigger the right content for the right customer at the right time.
In our day-to-day lives, we expect our Amazon Prime histories to contain a complete record of everything we’ve ever bought and provide recommendations of things we might like to buy in the future. On mobile, our news algorithm offers up only stories we might be interested in based on past clicks, and even the ads we see on social media are specifically tailored to our individual interests. Personalized communication based on our entire history is what we’ve come to expect in our online interactions as consumers — what about in our interactions as employees?
Personalization in the B2B world is far behind its B2C counterpart. But let’s take sales for example — imagine if a CRM were able to offer sales teams a complete, cohesive overview of the customer. How much more attention and energy would those salespeople be able to offer prospects and clients?
Currently, individual elements of the sales process are often managed by different departments, which employ cumbersome, slow, and even manual methods. At the center of the sales process is the CRM, but the traditional CRM hasn’t kept pace with the changing climate of the buying process.
Here are a few ways old-school CRMs aren’t cutting it — and how an improved, more personalized CRM might make a huge differenceCRMs are too passive
The first customer relationship management tools widely available to businesses completely revolutionized the ways we understood our customers. Most businesses went from pages and pages of tedious spreadsheets to having at-a-glance, easily searchable information at their fingertips.
However, for too many businesses, CRM technology has petered out at the digital Rolodex stage, which means missed opportunities for both marketing and sales because customer data is often disconnected and incomplete.
While the CRM has evolved to support and integrate with other sales process tools in an attempt to deliver value to the sales rep, the experience is lacking. Disconnected sales tools attempt to create a complete customer view, but lack the intelligence to analyze the collective data. That leaves reps scrolling through account, contact, and opportunity records to piece together the puzzle of the customer.
Instead of housing disconnected bits of data, the CRM should actually act as the central nervous system of the sales process, meaning it should house your sales rep’s hottest leads, along with what points those leads visited on your website, what solutions customers currently use, what other solutions they’ve tried, and what engagements they’ve had with an organization.
An AI-based CRM can take these insights one step further, offering recommendations that will help sales reps augment the art of selling.
Sales forecasts aren’t a priority
Having an outdated CRM that seems like simply a storage spot for customer information with no real, connected insights into customer behavior is frustrating.Not just for sales reps who are trying to identify and contact new leads, but also for sales leaders hoping to make accurate sales predictions.
Currently, the sales forecasting process relies mostly on “gut instincts” — a sales manager sitting down with a rep and reviewing deals in the pipeline using the often incomplete pictures painted in the CRM. But there’s a better way.
Imagine a CRM that offers rich visualizations to show what’s changing in the forecast, in real-time — enabling your managers to coach their teams on the best next steps in their deals to increase close rates and speed up cycles. AI-based CRMs combine human insight with machine intelligence. And that combination might just mean the difference between a defined roadmap for sales and a shot in the dark.
Sales teams don’t have all the information they need
It takes more than talent to be great at sales, and even the best salespeople need some help by way of a streamlined, company-wide process for selling. According to an evaluation of over 700,000 sales associates, a full 74% of salespeople were determined to be “failing.” The study suggested that the main factor was that “most people who go into sales have no formal training about how to sell,” as well as a lack of established company processes. And all too often, our sales coaching process is focused on backward-looking metrics such as quota, as opposed to real-time key performance indicators.
Instead of reviewing footage the day after the big game, sales coaching that relies on real-time metrics could give sales associates a better look at what’s going wrong and what’s working in their approach to sales.
A relatively simple fix for coaching sales teams through the process is to set up sales enablement portals. By combining all the documentation and content needed to guide the rep through the sales process in one dedicated area, much of the improvisation and disjointedness prevalent in more traditional sales approaches is fixed.
Managers armed with technology-enabled real-time data about their reps’ progress can conduct periodic coaching sessions that are focused on actual improvement. Constructive, AI-assisted coaching uses real data to shed light on the current state of a rep’s progress and focuses ahead to help foster an atmosphere of proactive improvement.
Amazon’s Prime Day wasn’t successful only for retailers but also for advertisers who tapped into the online shopping event’s success. Here are the key stats you need to know and what to do next.
Amazon’s Prime Day was their ‘biggest shopping event’ up to now with members buying more than 175 million items worldwide in two days. Retailers saw a big increase in their sales and even other sites benefited from the online shopping spree.
Key stats include:
Prime members worldwide saved more than one billion dollars throughout Prime Day.
Members in 18 countries shopped – double the number since the first Prime Day five years ago.
A record number of Prime members shopped during Prime Day in the U.S.
Amazon welcomed more new Prime members on July 15 than any previous day, and almost as many on July 16 – making these the two biggest days ever for member signups.
According to Jeff Bezos, Amazon Founder and CEO:
“Members purchased millions of Alexa-enabled devices, received tens of millions of dollars in savings by shopping from Whole Foods Market and bought more than $2 billion of products from independent small and medium-sized businesses. Huge thank you to Amazonians everywhere who made this day possible for customers.”
Except for the sales, there was also additional revenue coming from the advertisers who wanted to benefit from the increased interest in Amazon’s site these two days.
In fact, advertisers were encouraged to increase their spend to make the most of the big audience that could turn into potential customers for them.
The growth of Amazon advertising
Amazon’s advertising business has become very profitable. There is annual revenue of $10 billion from selling ads and there is an estimate of further growth.
In fact, Amazon is currently the third-largest digital advertising platform in the US after Google and Facebook. According to eMarketer, Amazon will claim 8.8% of US digital spend in 2019, which is a great increase from 6.8% in 2018.
There are many ways to make the most of Amazon advertising especially on busy days like Prime Day.
The idea of using sponsored posts, display ads and even video ads can help advertisers promote their products even when they are not selling them directly on Amazon.
Amazon ads can also help you gain valuable insights on consumer habits and the best ways to approach your prospective customers through the right messaging.
This is something that can be very useful during busier periods such as Prime Day.
Advertising success during Prime Day
Prime Day allowed advertisers to benefit from a busy shopping event that brought them closer to a new audience.
Kenshsoo looked at their ecommerce performance data to find out how advertisers reacted to Prime Day.
The findings were very interesting:
Advertisers spent 3.8X on Prime Day compared to any other day in July.
What’s more interesting is that they also generated 5.8x of their usual revenue on any other day in July
Kenshoo advertisers who joined Prime Day last year spent 2x the budget on the first day of Prime Day in 2019
The most popular categories for increased spending were Toys & Games, Health & Beauty, Computer & Electronics, and CPG
When looking at the spending, advertisers spent 6.8x in Toys & Games ads compared to last year, 3.1x in Health & Beauty and 2x in Computer & Electronics
What we can learn is that there is a growing interest from advertisers to tap into Amazon’s Prime Day. The success of the event will spark even more interest in the future, which comes to the importance of planning ahead and setting up an advertising strategy that will beat the competition.
It’s also useful to look at the specific categories that saw an even greater growth from last year to explore how you want to benefit from big shopping events in the future.
Opportunities with Amazon advertising
Advertising on Amazon can help you improve brand awareness but also reduce the sales cycle.
From finding out more about your target audience to making your funnel shorter through the right actions, the opportunities are numerous and diverse.
As the third biggest ad platform in the US, it is becoming easier to justify your ROI by creating ads that speak to your target audience.
Amazon’s ambitious plans for its advertising model and the estimates for a bigger interest in it, and thus revenue, indicate that paid search can facilitate the shopping decisions both for consumers but also for retailers who want to promote their products.
Prime Day seemed like the perfect event to increase the ad spend so the next challenge is to use the learnings from the two busy days to set up a long-lasting plan that will bring even greater success.
In April, IBM said it was spinning off its Watson Marketing division to private equity firm Centerbridge Partners. This week, the new company announced its new name: Acoustic.
Listening vs. surveillance
The branding raises two main questions about the direction of this marketing platform, built around IBM’s Jeopardy-winning supercomputer system, Watson: the value of this new name, and the market position for this new company.
In its announcement, Acoustic CEO Mark Simpson said that the new name represents the company’s attitude that “only by listening carefully to consumers can marketers make themselves heard.”
IDC Research Director Gerry Murray told ClickZ via email that, while Acoustic is “all about listening,” and that can be a good foundation for a customer-centric message, they need “to be careful about slipping into the surveillance trap.”
In these days of growing privacy and consent rules, he noted, there’s a big difference between listening to customers so you can respect “their intentions” — and “listening to everything all the time so you can make probabilistic guesses about engagement.”
The new Acoustic Marketing Cloud will offer experience analytics, content management, personalization, customer journey analytics, promotion capabilities, a payment gateway and campaign automation like email marketing, all of which will utilize Watson’s automated recognition of textual and spoken natural language, and of still images and video.
Analyst David Raab pointed out to ClickZ via email that Acoustic is “built from a large collection of products that IBM purchased, so the company’s challenge will be to harmonize them (get it?) into a properly integrated system.”
He said that the “real question is whether being freed from IBM will enable the management to be more agile and focused.”
Murray said that Acoustic’s differentiators could include the use of AI, microservices and open APIs to deliver data, analytics and recommendations across the applications.
“The market is no longer about best of breed,” he said. “It’s about optimal orchestration.” In that sense, he added, “they are not that different from other major marketing cloud providers that are still working on integrations between many acquired code bases.”
Although marketers’ preferred advertising mediums have changed over the decades from print and radio to television and online, how they use ads to interact with consumers has remained largely unchanged. It’s always been a one-way street with the brand presenting itself to the consumer in an effort to compel the audience/browser to take action.
The proliferation of powerful mobile devices and apps enabled advertisers to move away from the static banner ad to more dynamic ad units. While rich media formats offer more interactivity within an ad, there is no real interactivity between the brand and consumer, and engagement rates are declining. But thanks to rapid advancements in natural language processing (NLP) and machine learning that have given rise to conversational AI technologies, marketers can realize the vision of creating true two-way interactions that engage customers in brand journeys and prepare them for push-based re-engagement.
Start a conversation
Facebook’s Click-to-Messenger conversational social ad unit and Google’s AdLingo conversational display unit are two platforms marketers can leverage to create AI-powered conversational display ads that offer a customizable user experience that consumers will find much more engaging. This enables a brand to create a personalized one-on-one experience based on real-time conversations with a consumer, and do so at scale.
The critical component of Click-to-Messenger and AdLingo is that a brand can embed its conversational assistant inside any interactive display ad unit. Instead of having to draw consumers into their own website or app, consumers can start a conversation while they’re viewing and interacting with a display ad. That interaction is seamlessly moved to the conversational AI platform, and the consumer can ask questions, conduct research, and provide feedback. They receive the help and information they need immediately and without navigating to other pages. Each conversation is user-driven and mirrors the experience of speaking to a sales associate while standing in a store aisle, or on the phone with a customer service rep. Just as importantly, customers can share their experiences with their friends in the same application.
Get the message?
The word “messaging” is a broad umbrella, and not all messaging apps and platforms are as effective as others. It’s important to draw a clear distinction between posting updates and comments to the Facebook feed and Facebook Messenger. There are more users on the Feed, but Messenger can be tightly integrated into a brand’s call to action, it is less cluttered, the audience is more diverse, and more people use Messenger on mobile. Messaging apps contribute to a higher percentage of user engagement time vs. traditional mobile apps. Particularly on a mobile device, these apps offer a very valuable opportunity to re-engage a user, even when the brand isn’t necessarily top-of-mind.
The email has become negatively impacted by spam and phishing attacks and isn’t engaging younger audiences as much as it does older demographics. SMS is limited due to restrictions on the size of messages, a largely text-only experience, clunky-to-no support for rich media and the fact that it’s being increasingly impacted by spam and phishing attacks.
Rich Messaging Solutions such as Facebook Messenger deliver better user engagement and ROI for brands. They are more interactive and allow for measuring and reporting intent, sentiment, and needs of the end consumer. This enables brands to apply machine learning to collect, analyze, and use the ever-growing volumes of customer data they’re collecting (always with the customer’s explicit permission) to create highly personalized engagements. The resulting “conversations” are the key to driving long-term engagement.
Conversational commerce on a global scale
This is not a hypothetical scenario. Consider just how popular the social media messaging app, WeChat, has become in China. Users can interact directly with third parties to do almost anything from making purchases, sharing photos and videos, hailing a car from a ride-sharing service or booking a restaurant reservation.
The technology has gained traction across Europe too. Quandoo, one of the world’s fastest-growing restaurant reservation platforms globally, offers consumers a wide variety of dining experiences from Michelin-starred restaurants to local favorites. Restaurateurs use Quandoo’s reservation management platform to drive transactions and engage with their customers via Facebook Messenger.
The Quandoo-Facebook Messenger combination that offers search and discovery via natural language commands is much easier to use than a mobile app like Yelp! or OpenTable. It also facilitates conversations among all members of a party when everyone’s weighing in on where to eat, when to meet up, how to get there, and when posting reviews. It’s a much more engaging experience than what a mobile app can deliver, and that also enables Quandoo to more quickly expand its potential customer base.
We’ve seen this before, a mobile technology gains wide adoption in Asia and Europe, and by the time it gets to the U.S. it’s a billion-dollar opportunity. We saw that happen with mobile devices, SMS, ringtones, music services, and now mobile advertising. This presents the opportunity for U.S. companies to get ahead of that wave.
The technologies exist that enable you to create and leverage ads within online platforms and messaging apps that drive personalized conversations between you and consumers. While the consumer is engaged, the technology works in real-time to score all input for sentiment and intent to continue the interaction, or seamlessly hand-off to a human agent when appropriate. You can offer persistent, personalized, messaging-based experiences across a large, and ever-expanding diversity of “conversational surfaces” to improve initial customer engagement on social media feeds, draw them into your sales funnel and build long-lasting relationships.
Mahi de Silva is CEO of Amplify.ai. He can be found on Twitter @Mahi.
Forrester evaluated and scored the top 11 B2C commerce suites in late 2018 in their Forrester Wave report. Top contenders were commercetools, Digital River, Elastic Path Software, Episerver, IBM, Kibo Commerce, Magento, Oracle, Salesforce, SAP, and Sitecore. Of those, SAP and Salesforce led the pack. What made them pull ahead of the rest?
Analysts looked at thirty-one criteria in their scoring. The report highlights three of the most important areas they weighed:
Impactful experience, specifically driven by search, personalization, promotions, and AI-infused analytics. The report summarizes this as “the ability to target content and products with shopper incentives across the shopper journey.”
Business user empowerment, considering not just functional capabilities, but how well a platform attracts and incentivizes customers and responds to shopper demands.
Operational efficiency, looking at if the platform lets users easily upgrade versions with no recoding and minimal regression testing.
IBM, Oracle, Magento, Kibo Commerce, and Episerver were all “strong performers.” Contenders included Sitecore, Digital River, commercetools, and Elastic Path.
Image provided by SAP
The report also breaks down the analysis via a scorecard for each platform in some dozen categories spanning sales channel support, personalization, AI and machine learning, support services, and product vision, among others.
On this scorecard, both Salesforce and SAP scored a 5.0 (out of 5.0) in AI and machine learning. SAP earned a 5.0 in sales channel support and product vision as well, while Salesforce scored higher in personalization and business intelligence.
SAP offers a full-featured suite for enterprises
“SAP Commerce Cloud is a best fit for companies looking for an industrial-strength, full-function commerce platform in wide use across several industry verticals,” the report says.
SAP’s full-featured suite has a 50/50 revenue split between B2B and B2C clients, and “is equally adept at both,” Forrester writes.
They also note that the company has invested heavily in its cloud strategy, and is reaping the benefits of doing so: “half of its 2017 commerce revenue came from its cloud offering,” they note.
Forrester also mentions SAP’s “outstanding enterprise customer references who reported seamless scaling and load management for billion-dollar GMV loads.”
According to one such glowing review from an enterprise customer, “We can ramp to a million transactions a day with no concerns; the platform is rock solid and enterprise-ready.”
Salesforce also a leader but with a shared revenue model
Salesforce B2C Commerce has long been another major player in the retail digital commerce space, supporting over half a billion unique monthly shopper visits across the globe.
The report does find the platform isn’t without drawbacks, though. For example, Salesforce B2C Commerce’s coding customization is more expensive than for other platforms.
Analysts note that Salesforce’s option would work for retailers that are “looking for an out-of-the-box cloud solution and are willing to accept a shared revenue model.”
What could the “strong performers” do better?
Adobe’s Magento is among the next best platforms, according to Forrester’s report. It’s a “best fit for clients that are looking to customize their solution, value the open source model and its extensive ecosystem, and want an affordable alternative,” analysts note. However, some of its features remain “substandard,” including weak native content management tools, slow indexing, and search results lacking in relevance.
IBM’s commerce suite also ranks highly in this report, though analysts write that its “ comprehensive, if unwieldy, solution needs to modernize more quickly.” The fact that they’ve been a presence in the enterprise commerce market since the 1990’s — and that they’ve been continually adding functionality since then — has led to their platform being full-featured but also “large and cumbersome,” the report observes.
Oracle’s Commerce Cloud is a bit newer to the market — the platform has only been live for two years (as of Q3 2018) and “is still gaining adoption, reference customers, and stability,” the report finds. At the same time, Forrester remarks that the platform has strong potential, particularly when linked with the Oracle Data Cloud.
Kibo Commerce is one of the smaller vendors mentioned in this report, with a primary focus on the North American market. On the positive side, Forrester notes that customers “liked working with a responsive, small vendor,” and that price was a strong selling point. On the other hand, customers voiced concerns around stability and “rudimentary” analytics capabilities, as the platform is still maturing.
Marin Software surveyed nearly 500 digital marketing decision makers in May and June of 2019. The survey included marketers from B2B and B2C companies, each of whom are responsible for an annual digital advertising spend of between $1-9 million (69%) and 10M-49M (31%).
The survey found that the top priority for marketers this year is in increasing brand awareness, followed by enhancing customer experience. At the tactical level, 20% of respondents indicated a that they are embracing omnichannel marketing and social media. Optimizing paid search was also a top tactical priority, proving that paid search remains a key initiative for top marketers in 2019.
Source: Marin SoftwarePaid search dominates the digital ad landscape
Paid search is the clear winner when it comes to digital ad spend, with respondents indicating that paid search comprises 40% of their digital ad budgets. This is about twice as much as the second highest contender—paid social which comprises just under 20%. Other top channels include display, YouTube, Mobile/In App ads, ecommerce (Amazon), and ecommerce (other).
Source: Marin SoftwareThe top challenges differ across channels
Survey respondents were asked to list their top challenges across three channels—search, social, and Amazon.
Meeting volume and efficiency goals were cited as the top two challenges for paid search, with 29% and 28% of respondents listing these as key challenges in 2019. Integrating product feeds was also listed as a paid search challenge by 27% of respondents.
The top paid social challenge was attribution/cross-device measurement, followed by generating quality creative and brand safety.
Amazon is a relatively new player in the digital ad space, so it’s no surprise that 32% of respondents listed leveraging audience data (first and third party) as the top challenge with this channel. 30% of respondents indicated that understanding Amazon advertising techniques posed a challenge.
Source: Marin SoftwareGoogle, YouTube and Amazon top the list of most trusted publishers
Data privacy is a big concern among advertisers, particularly with the EU’s implementation of GDPR last May. Respondents were asked to rate a list of top publishers based on a trust index from 0 to 5 (with 0 being the least trusted and 5 being the most).
Google came out on top, with a trust index of 4.5, followed by YouTube at 4.3. Other top-trusted publishers include Amazon (4.2) and Facebook and Instagram (each at 4.1). The least trusted publishers were Verizon, Pinterest, and Bing.
Respondents listed data privacy, tracking restrictions and ad blocking as some of the top challenges or trends impacting their business this year, along with video advertising. Other impactful trends and challenges include visual search, ad fraud, brand safety, influencer marketing and messaging apps/bots.
Source: Marin SoftwareA few words about Amazon
Amazon is an up and coming player in the mix of digital ad publishers, with fully 60% of respondents indicating that they are increasing their Amazon budget this year. Nearly all respondents indicated that this budget will be incremental and will not cannibalize existing ad budgets.
Advertisers see Amazon as source of growth, with 18% of respondents utilizing it to capture people at the start of the buying journey.
Amazon’s DSP platform which serves display and video ads on Amazon and partner sites such as IMDb is the preferred format of survey respondents, with 43% indicating they are currently using it. Sponsored products and sponsored brand ads are utilized by 40% and 39% of respondents, respectively.
Trends that will influence 2020 spending
Marin asked respondents about the most popular trends in digital advertising including what tactics they’ll continue to implement in 2020.
Responsive Search Ads—an ad format that Google introduced in mid 2018, is a top trend in 2019 with 83% of respondents indicating they currently use them or plan to use them this year.
Shopping ad usage is also a growing trend, with 65% of advertisers indicating their shopping ad spend will increase in 2019 versus 2018. Shoppable images and shopping ad spend on paid social is also a growing trend with more than 60% of respondents indicating they expect their company’s use of these ads will increase this year compared with last.
Respondents indicated that the most effective social ad format in 2019 was video (32%) followed by stories (23%). Other top social formats include feed banner ads and carousel ads. We can expect to see ad spend increase on social platforms throughout 2019 and into 2020.
The full 2019 State of Digital Advertising report is available here (free, gated).