Monthly Archives: July 2019
Invoca, an AI-powered call tracking platform, published their Call Tracking Study Guide in March of this year. The in-depth guide demystifies call tracking technology and reviews how call tracking tools help marketers connect digital campaign data to inbound customer phone calls.
Call tracking is a powerful way for marketers to understand exactly where phone calls are coming from with granularity that, for the most robust tools, can extend down to the keyword level. This data helps reveal what platforms, publishers, keywords, and channels drive high-intent customers to call and can help marketers create a more informed media allocation strategy.
Content produced in collaboration with Invoca.
Call tracking 101: A brief introduction
The tag also captures various referrer elements such as utm source, medium, paid search keyword and Google click ID—this is what enables Invoca to connect user data to phone calls.
Example of dynamic tracking phone numbers on a landing page—source: Invoca
When the tracking number is called, the platform can also route the caller to the appropriate person or call center depending on what marketing content they are viewing, reducing time on hold and call transfers. Data is collected based on the specific call number which can include caller information, keyword, referrer type (e.g., banner ad, search ad, or social media ad) and referral source (e.g., Google, Facebook, etc.) which can also be used to inform the call center and create a highly personalized experience for the caller.
Example of referral data info in Invoca
Not all call tracking tools are created equal
There is a large selection of call tracking tools on the market that range from basic to advanced in terms of features and functionality.
Basic tools provide limited data to marketers, but they ignore the larger customer journey and tend to focus on last-touch attribution (e.g., making it difficult or impossible to determine where the call came from).
Some metrics a basic tool might track include:
- Call volume
- Call time and duration
- Caller information
- Basic campaign attribution
These tools provide some sense of campaign performance, but fail to tell the full story that can be gleaned when connecting analytics platforms (e.g. Google Analytics) to call information.
More advanced AI-powered call tracking tools like Invoca aim to bridge that gap, while also automating some marketing actions after the call takes place.
Advanced capabilities that AI-powered call tracking tools provide include:
- Touchpoint attribution—Tie a call back to its source such e.g. paid search or social
- Data unification—Integrate with multiple online (and offline) sources such as CRM tools
- Data analysis—Use AI to analyze phone conversations and provide insight on call drivers, behaviors and outcomes
- Marketing integration—Push data to the marketing stack for automation, optimization, analysis and more
The end result—and key benefit—of implementing an advanced call tracking tool is to gain valuable insight about campaign performance and attribution.
Call tracking 201: AI and machine learning
Martech companies are increasingly powering their technology with AI-driven platforms. AI enables marketers to gain intelligence quickly and make better-informed decisions. This trend bridges multiple industries, as shown in the graphic below.
Companies that utilize or provide AI technology—source: TOPBOTS
Invoca uses Signal AI to help measure and attribute online conversions by mining data from the phone conversations themselves, freeing up valuable time for marketers who no longer have to listen to every call.
Signal AI uses AI to detect intent and patterns in language to provide actionable insights and conversion data (sale made, appointment set, etc.) for marketers. This is accomplished through a series of steps that start with the recorded conversation, transcribing the call into text which can then be analyzed by an algorithm, identifying key patterns, phrases, and actions, and pushing these insights to your marketing stack. Here’s a visual of what that looks like. Note that Invoca does not save call transcripts and is HIPAA and PCI compliant, an important distinction for marketers concerned with data privacy.
Image source: Invoca
Signal AI uses machine learning, an application of AI, which gives machines access to the data so that they can learn from it. AI works in conjunction with machine learning to provide actionable and accessible data to marketers—but marketers still need to review this data and make decisions based on their own observations and conclusions.
Invoca offers two versions of Signal AI to their call tracking clients. Pre-trained AI uses industry-based predictive models that have been “pre-trained” using thousands of hours of call data.
Custom AI is more appropriate for certain businesses, such as those with high volumes of calls or sophisticated data needs. This more complex option takes longer to create and implement, however, it can help certain businesses predict call outcomes with a higher degree of accuracy.
Debunking some common assumptions
Skeptics may think that humans can classify calls more efficiently and accurately than AI, but the truth is the opposite. AI learns over time and it never gets tired, so it’s an effective and accurate way to classify calls without bias. Here are some other call tracking myths, debunked:
- It’s hard to set up AI-based call tracking—Pre-trained AI models take the guesswork out of setup for certain industries such as insurance and can identify the most common outcomes (e.g., product purchased).
- All AI-based call tracking is the same—False! Invoca’s Signal AI uses predictive analytics (rather than just transcription) and continues to learn. It also provides performance scoring for easy reference.
- Only big companies can afford AI-based call tracking—Wrong again. Invoca is tag-based and easy to implement. You don’t need a dedicated IT team or programmer to get up and running.
Clear strategy and clean data
The true power of AI-based call tracking is, in a word, attribution. It’s the ability to unify call data across multiple sources and attribute it to all consumer touchpoints.
Invoca does this by collecting data from multiple sources: campaign and website data, first-party data (e.g., pulled from your CRM), third-party demographic data, call data such as length, time and location of call, and conversational data (derived from speech analysis).
Once all the available data is unified, Invoca’s technology determines the value of the call by analyzing the spoken conversations within the calls. Invoca’s AI synthesizes various word patterns (e.g., “I’m almost ready to buy, but I’m waiting for XYZ to happen”) and then classifies them into useful datasets.
Signal AI helps predict the type of call (e.g., sales, service, complaint) which allows marketers to optimize media placements, ad content, and more. This level of analysis can also help inform the call experience itself by identifying issues that may frustrate callers.
Connecting call data to campaign data can help in other ways too. For example, marketers can use call information for ad suppression, making sure customers don’t see offers for something they’ve already purchased or retargeting ads to people who called but didn’t make a purchase.
Tying it all together
One of the most powerful features of the more robust, high-end call-tracking tools like Invoca is the ability for them to integrate with existing marketing platforms like Google Analytics, Adobe Experience Cloud, and Salesforce.
This gives marketers a clear picture of where their customers are at every step of the journey. It closes the attribution loop, allowing you to demonstrate what’s working from an ROI standpoint, a metric that’s key when it comes time for approval and budget allocation.
When considering implementing a tool like Invoca, the bottom line is always the top priority—will we make money with this martech investment?
Invoca customers have seen up to 60% increase in conversions when implementing the tool (without any additional media spend), an important consideration when factoring in ROI.
The Invoca Call Tracking Guide covers all this including what questions to ask vendors when considering a new tool and what to consider when shopping for a call tracking solution.
To learn more about call tracking technology from functionality to implementation and how call tracking can help with campaign optimization and attribution, download Invoca’s whitepaper, “The Call Tracking Study Guide for Marketers.”
The post Guide to call tracking and the power of AI for analyzing phone data appeared first on Search Engine Watch.
Ford, Honda, Volkswagen, and BMW agree to tougher California mileage standards, potentially disrupting Trump’s proposal to relax US rules.
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Senate Democrats want to remind everyone that US elections are still at risk, and Congress could do more to protect them.
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Midwest Digital Marketing Day is an intentional event focused on creating a space for shared learnings and communication with our fellow PPC heroes in the heartland. We know that working in digital marketing in the Midwest means we’re spread out, and it’s harder to find meet-ups and swap ideas. This event is designed for connecting with fellow marketers and deepening your PPC skills.
Read more at PPCHero.com
Last July, Google announced its Contact Center AI product for helping businesses get more value out of their contact centers. Contact Center AI uses a mix of Google’s machine learning-powered tools to help build virtual agents and help human agents as they do their job. Today, the company is launching several updates to this product that will, among other things, bring improved speech recognition features to the product.
As Google notes, its automated speech recognition service gets to very high accuracy rates, even on the kind of noisy phone lines that many customers use to complain about their latest unplanned online purchase. To improve these numbers, Google is now launching a feature called ‘Auto Speech Adaptation in Dialogflow,” (with Dialogflow being Google tool for building conversational experiences). With this, the speech recognition tools are able to take the context of the conversation into account and hence improve their accuracy by about 40 percent, according to Google.
In addition, Google is also launching a new model phone model for understanding short utterances, which is now about 15 percent more accurate for U.S. English, as well as a number of other updates that improve transcription accuracy, make the training process easier and allow for endless audio streaming to the Cloud Speech-to-Text API, which previously had a 5-minute limit.
If you want to, you can also now natively download MP3s of the audio (and then burn them to CDs, I guess).
Marketers and Marketing Analysts generally depend on the tools or IT department to help them pull the data for marketing purposes. There comes a time when they can’t just wait around for IT to help them data pulls and manipulations. They have to know how to do it on their own. This course is for those marketers who would like to know how to use SQL to conduct their marketing analysis.
The course uses MYSQL to show how SQL works but all the leanings and syntax are applicable to other databases as well. Sign up for SQL for Marketers and Marketing Analysts
Whenever I speak to Nonprofits (which is something I love to do), I always evangelize the importance of leveraging all of the online technology companies which offer “in-kind” services, especially Google Grants. However, for marketers in today’s world, Google Grants is simply not enough. Identifying with potential donors, volunteers and simple awareness has evolved way beyond the search engines and into our Facebook and Twitter feeds as we all crave instant news, gossip and basic information. In this post, I will discuss not only the steps that have already been taken by Facebook, but also how much more they need to do to fulfill their obligation to assist those organizations in need.
What Facebook needs to Learn from Google
In the early months of 2002, Google relaunched its AdWords platform with a new cost-per-click (CPC) pricing model that made it increasingly more popular and successful with both large and smaller companies. It was this achievement that opened the eyes of both the Google founders and other Google executives, to provide the same opportunity for Nonprofits by giving them free ads on Google.com. In essence, they believed that the Adwords platform would enable non-profits too reach a much larger audience and connect with the people who were searching for information about their specific cause or programs. As you will see below, it has grown by leaps and bounds….
Screenshot from the new Google Grants Blog:
Why Facebook Doesn’t Understand the Opportunity
After seeing the success of Google grants for the past 13 years, you would think Facebook would have a Nonprofit plan already in place to offer Free advertising to Nonprofits. However, it appears that even though they have made attempts to achieve this, it was simply not enough. According to the great article by AdWeek entitled: “Nonprofits Rely Heavily on Social Media to Raise Awareness“, author Kimberlee Morrison mentions that the social media presence is growing significantly for nonprofits. She goes on to say: “The report shows an increase of 29 percent in Facebook fans across all verticals and a 25 percent increase in Twitter followers. What’s more, there are big increases in sharing and likes from sources outside the follower base, so it would be wise for nonprofits to play to that strength on social sites if their aim is attracting a wider user base.”
How Facebook Failed in its First Attempt
Back on November 15, 2015, The Nonprofit Times published an interesting article entitled “$ 2 Million In Facebook Ads Going To Nonprofits” in which Facebook announced in partnership with ActionSprout, that they will distribute $ 2 million in Facebook Ads credits during the holiday season. These Facebook Ads credits (up to $ 1,500 each) will be given out to roughly two-thousand nonprofits. According to author Andy Segedin, he states that “…according Drew Bernard, CEO and co-founder. Organizations will receive credit allotments of $ 600, $ 900, $ 1,200 or $ 1,500 that will be granted from December through February. All applicants will be set up with a free ActionSprout account, Bernard said.“
The article goes on to say: “Bernard hopes that the credit giveaway will help organizations post more and better content on Facebook. The company plans to publish key findings based off of the distribution and use of the credits, but will not move forward with any follow-up efforts until information is gathered. “This is a test to see what we can learn, and with what we learn we’ll all go back to the drawing board and see if there’s something we should do next with this”.
If you are interested in hearing more about the “key findings” of this test, your going to have to wait a little while and also give them your email address. (Not very Philanthropic)
If you can tell by my tone, I am somewhat disappointed by Facebook’s lack of initiative with their efforts to help Nonprofits. In my opinion, they offer a much stronger platform than Google Adwords based on their “intense” targeting as well as their “ripe and persuasive audience”. I am also quite shocked that they could not follow in the footsteps of Google’s 13 years of supporting Nonprofits with their Google Grants Programs. To end insultr to injury, I am also dumbfounded that they not only had to partner with another company but also label their efforts as a test to limited number of Nonprofits for just a couple month. What’s the point of a test, when you know Nonprofits could only benefit from the Free Advertising.
You almost get the sense that this was for the benefit for everyone else, except for the Nonprofit which needs it the most.
Twitter is testing a new way to make conversation threads easier to follow, with the launch of a new test that labels notable replies with special icons. If the original poster replies somewhere in the thread, their tweet will have a small microphone icon next to their profile picture. Other tweets may be labeled, as well — including those from users who were mentioned in the original tweet and replies from people you’re already following on Twitter.
These will be labeled with the at symbol (@) and a small person icon with a checkmark by it, respectively.
The new test is the latest in a series of experiments Twitter has been running focused on making its product easier to use, particularly when conversations around a tweet become lengthy.
At the beginning of this year, the company began a test where it labeled as the “Original Tweeter” the original poster in a conversation thread. That may have been a bit too confusing for some, because a few months later, Twitter changed it to “Author.” It then also added two other labels, for people who were mentioned in the original tweet and those replies from people you’re following.
We're testing icons instead of labels within replies. Check it out and let us know what you think! pic.twitter.com/5CBoTZ40Hq
— Twitter (@Twitter) July 18, 2019
These, however, were text labels — meaning they took up valuable screen space on small mobile devices. They also cluttered up the already text-heavy interface with more distracting text to read.
The new icons don’t have that problem. But they’re also small and light gray and white in color, which makes them hard to see. In addition, their meaning isn’t necessarily clear to anyone who doesn’t hang around online forums like Reddit, for example, where it’s common to use a microphone to showcase the original poster’s follow-up comments.
It’s also unclear why Twitter thinks users are clamoring to see this information. Highlighting the original poster is fine, I guess, but the other labels seem extraneous.
While this is a minor change, it’s one of many things Twitter is tweaking in the hopes of making its service simpler and more approachable. It’s also running an experimental prototype app called twttr where it’s trying out new ideas around threaded conversations, like using color-coded replies or branching lines to connect tweets and their responses.
A lot of these changes feel a little unnecessary. Twitter isn’t as difficult to understand as the company believes it is.
At the end of the day, it’s a way to publish a public status update and reply to those that others have posted. That’s its core value proposition — not live-streaming video, not its clickable newsreels it calls “Moments” and not its article bookmarking tools. Those are useful and fun additions, sure, but optional.
Instead, Twitter’s challenges around user growth aren’t because the service is overly complex, but because a public platform like this is rife with issues around online bullying and abuse, disinformation and propaganda, hate speech, spambots and everything else that an unmoderated forum would face.
Twitter tests are live now, but may not be showing for all users.
Soon the company will begin placing anxiety-relieving exercises within its search results to help boost your mood.
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