The Importance of a Marketing Tech Stack

techmanga June 27, 2021 0 Comments

Analytics and quantitative research

Clean data for quantitative research is an essential starting point for anytest and learn program.Analytics data will inform the initial story of your customer journey; it willenable you to prioritize test areas and gain insight into your customers’goals and intentions. We group these into two buckets: Primary analytics andsupplementary analytics providers.Primary Analytics: There are really two key players that provide primaryanalytics reporting for most organizations: Google Analytics and AdobeAnalytics. Together, these two have a lock on around 75% of the market. Googledominates for websites of all sizes, however, Adobe can’t be discounted,particularly as a solution amongst high-traffic Enterprises.Another company to keep on your radar is Heap Analytics. Heap has emerged as apowerful solution known for its ease of implementation and ability to auto-tagall site activity. For companies with limited IT resources, this single-lineof javascript implementation is an attractive option.Supplementary Analytics: While Google and Adobe dominate as primary analyticssolutions, there are many emerging technologies you can use to supplement thedata your primary tool is collecting. These tools provide advanced solutionsfor data visualization, marketer-friendly tagging, and prescriptive analytics.These solutions may not be worth the expense for smaller organizations inearly stages of experimentation maturity. But when you start asking verycomplex questions and dealing with larger data-sets, your primary dataanalytics tool can become restrictive.Companies that are looking to take their analytics game to the next levelshould look into:With a solid analytics set-up, your team can start to uncover the low-hangingfruit within your digital experience and identify opportunities for testing.You will quickly find, however, that you need to implement an experimentationtool to increase the confidence you have in the changes you are making.

Advanced experimentation & personalization: Data and customer management

technologiesWe hear shouts of “hyper-personalization” constantly—a one-to-one customerexperience is the pinnacle for many organizations today. Of course, thisrelies on the existence of underlying data to define what makes an experience“personal.” Most organizations do not have the proper technology in place toenable this.If your business has been struggling to do effective personalization, youshould 1) interrogate your overall personalization strategy, and 2) lookclosely at how you are managing your customer data.The proper use of a robust customer data platform (CDP) is a key componentthat differentiates mature test and learn programs from the immature. Theseplatforms open up the world of audience management, boosting your ability toidentify and target high-value audience segments and plan test strategiesaround these groups.

Customer Data Platforms (CDP)

The CDP Institute defines a Customer Data Platform as “packaged software thatcreates a persistent, unified customer database that is accessible to othersystems.”A major benefit of a CDP is the ability to deliver a more effective customerexperience and more impactful marketing messaging. (Which is really the goalwith personalization). Your customers want a consistent experience across allof the channels and devices they’re using. They don’t want to see an ad forsomething they have already purchased. A CDP allows you to gain a completeview of your customer and deploy a consistent experience across touchpoints.It is important to note, however, that a CDP is only as useful as it iscomprehensive and actionable. This means that the number of data sourcesavailable to your CDP, as well as the number of execution integrations areboth critical.> Most organizations do not have the proper technology in place to enable 1:1> personalization.If you aren’t collecting data from multiple sources—website, mobile app,customer service system, in-store behavior, beacons, etc.—you may not be readyfor a CDP. As well, if you can’t activate this data across multipletouchpoints—website, in-store, customer service interactions, etc.—you willnot unlock the full potential of a CDP to provide a truly unified customerexperience.A CDP is not a personalization tool. However, it provides the data that willallow you to get the most use out of your personalization and experimentationtool.If yours is a mature program and you are looking to enhance yourpersonalization efforts or improve your overall data management efforts,Tealium’s Universal Data Hub is a great choice. Evergage is also a strongsolution, combining a CDP with real-time personalization capabilities. If youalready have a data platform in place, Evergage also functions as a powerfulstandalone personalization platform.If you are looking for other tactical personalization solutions, you shouldalso evaluate Optimizely Personalization and Dynamic Yield.The business world has come a long way from the Mad Men era of focus groupsand hunches.Today, technology enables experimentation at scale. It allows organizations totest one experience against another, achieving a statistically confidentresult. Which greatly reduces risk in decision-making.However, it is vital that you define your experimentation strategy andultimate objectives before sourcing your technology stack. Choose tools thatfit these objectives, as well as your organization’s culture and the skilllevels on your teams.A final note: Before sourcing more tools, make sure you have a clear idea ofwhat your program constraints really are. You can install every tool on themarket, but that doesn’t mean you will have an effective experimentationprogram. First, you need a map of how you plan to get your program from A toB; technology is simply what you will use to pave the roads along the way.This article first appeared on Widerfunnel’s blog. Reach out to the author,Mike St Laurent or Get in touch with GO if you have any questions about yourtest and learn program’s technology stack. * Michael St Laurent Director, Experimentation and Product, GO > North America11 Essentials for Your Marketing Tech Stack in 2019Businesses that use marketing automation to nurture prospects experience a451% increase in qualified leads. (Annuitas Group) As 2019 approaches, it’stime to begin planning for digital marketing success in the new year. Nextyear, streamline your marketing processes with marketing tech stack tools toincrease overall efficiency and spare yourself a headache.Marketing technology is an ever growing aspect in the digital marketing world.Tools are a great investment for simplifying your workflows and keeping yourteam organized so you can focus on what matters. Take some time before 2019arrives to plan and build your marketing tech stack by starting with these 11essentials.

The Importance of a Marketing Tech Stack

While the term “marketing tech stack” may be new, the concept has been arounda long time. They simplify processes and the already hectic lives ofmarketers. So what is a marketing tech stack? Essentially, it’s a collectionof technology-based tools marketers use to streamline daily marketingactivities and increase overall efficiency. These tools help marketers adjustand adapt to the ever changing needs of their customers.Scott Brinker, Chief Marketing Technologist for Hubspot, is a big supporter ofutilizing a marketing tech stack. In fact, his own stack has grown from 150tools in 2011 to nearly 7,000 tools in 2018. With technology continuing toevolve, he expects that number to grow. We have come up with the top eleventools to maximize efficiency in 2019.

1. Content Management Systems

A content management system is essentially the base your website sits on, andone of the most essential elements of your marketing tech stack in 2019. A CMSsystem lets anyone, even those who don’t understand web development, easilymanage their website. While marketers typically wouldn’t change the design orfunctionality, as a developer would, you do have control over what content isposted to your site.Marketing Tech Stack Tool: WordPress An estimated one third of the visible internet runs on WordPress, with about500 new sites added daily. So it’s easy to say that WordPress is the favoredtool here. As stated on their site, “You don’t have to know a single line ofcode to publish content using WordPress.” It’s the easiest to use, most widelyrecognized, and best supported CMS platform, which is why many people aremaking the switch from other CMS.Marketing Tech Stack Tool: Hubspot Website Platform Hubspot allows you to manage all content: blog posts, landing pages, forms,site pages and emails from their home base. It also provides analytics—soeverything you possibly need to manage your site is all gathered in one easy-to-use hub.Marketing Tech Stack Tool: SquareSpace SquareSpace offers all the marketing tools you need to manage a website, witha heavy focus on the design and visuals your site will offer. It offersmarketing tools such as email campaigns, SEO, social integrations, analytics,customer engagement tools and blogging. SquareSpace also offers free,unlimited hosting and 24/7 security and support.Not sure how to budget for your tech stack? Download the 2019 DigitalMarketing Budget Template >

2. Advertising

The use of online advertisements has become more of a requirement than anoption to keep your business relevant in the digital marketplace. Having atool where you can build, manage and track your advertisements a key additionto your marketing tech stack in 2019.Marketing Tech Stack Tool: Google Ads By far the most widely used advertising platform (and for good reason), GoogleAds gives you the opportunity to reach a global audience, or target a muchmore defined, specialized audience. With a CPC pricing structure, Google Adsalso provides retargeting ads, which is necessary for pushing your leads tothe bottom of the sales funnel.Marketing Tech Stack Tool: Facebook Ads With Facebook ads, you can set your own budget and bid, target a very specificaudience, design an eye catching advertisement and then track the effects.Facebook also offers the option to run your ads on platforms beyond Facebookwith Instagram and Audience Network integrations.Marketing Tech Stack Tool: LinkedIn Ads LinkedIn offers a user-friendly advertising platform where you set your ownbudget using one of three options: total budget, daily budget or by settingbids (cost-per-click pricing structure). It offers an easy way to nurtureprospects using Custom Audiences to best attract and then re-engage yourtarget audience.

7. SEO

Search engine optimization is something many brands struggle to keep up with.Ever-changing algorithms, new websites and keeping backlinks clean are justsome tasks associated with SEO. It’s ideal to have a tool that can easilydetect what needs to be done, and even better if the tool can do it for you.Marketing Tech Stack Tool: Screaming Frog Screaming Frog is an “SEO spider” that crawls your website quickly to evaluateyour SEO. It returns information regarding broken links, auto redirects,duplicate content, page titles and metadata, XML sitemaps, data from the HTMLof your site and robots. Screaming Frog can integrate with your GoogleAnalytics account to take a look at things such as bounce rate andconversions. This is a great tool to clean up and focus your website in acontent audit.Marketing Tech Stack Tool: Google PageSpeed Insights You want your website to load quickly on all platforms, and this tool cancheck to see if that’s happening or not. You just input your website’s URL,and Google will return info regarding your page speed on mobile and desktop.They provide plenty of actionable, helpful solutions to improve your pagespeed, along with tutorials.Marketing Tech Stack Tool: Moz Local Search Simply plug your URL into this tool and Moz will show you where you rank onGoogle, Bing and other local search engines. You’ll be able to analyze yourlisting, review their suggested solutions and select a packaged solution toimprove your search listing.

9. Analytics

Having a full understanding of your audience and those who are interested inyour products is essential for marketing success. Having a tool that helpssort, organize and present this data to you in a comprehensible format isimportant to save time and energy.Marketing Tech Stack Tool: Google Analytics Google Analytics is by far the easiest and most user-friendly platform when itcomes to tracking analytics for your marketing strategy. It will show you howpeople use your site and outline actions to take to improve your business. Itoffers analytics intelligence, reporting, data analysis and visualization,data collection and management, data activation and integrations.Marketing Tech Stack Tool: SEMRush This tool is great for collecting specific analytics regarding organicresearch, advertising research, display advertising, backlinks, keywordresearch and product listing ads. It also provides plenty of tools to help youimprove or further automate marketing tasks in any of those categories.Marketing Tech Stack Tool: Cyfe If you’re looking for a broader scope in an analytics tool, this one may befor you. Cyfe not only offers analytics for marketing and social media, butalso client analytics, web analytics, finance, sales, project management andIT analytics. It truly is an “all-in-one business dashboard.”

11. Automation

If you want an all-in-one automation tool, we recommend using HubspotMarketing Automation. It has tools for: * Blogging * Landing Pages * Email * Marketing Automation * Lead Management * Analytics * CMS * Social Media * SEO * Call to Actions * Ads * Salesforce IntegrationWhen 2019 arrives, be prepared to effortlessly execute a successful digitalmarketing strategy using your marketing technology stack. Automating processesnot only relieves pressure from your entire team, but also keeps everythingorganized and convenient for your customers – ensuring everything runssmoothly in 2019. Download the free Marketing Budget Template to furtherorganize your marketing activities in the coming year.A cloud services cheat sheet for AWS, Azure and Google CloudByPublished: 06 Jan 2021AWS, Microsoft and Google each offer well over 100 cloud services. It’s hardenough keeping tabs on what one cloud offers, so good luck trying to get ahandle on the products from the three major providers.Even trying to compare what’s available in each cloud can quickly getconvoluted, since naming conventions vary by vendor and service. For example,you can be forgiven for not knowing AWS Fargate, Microsoft Azure ContainerInstances and Google Cloud Run all essentially serve the same purpose.So, if you ever feel at a loss for what’s what, hopefully this cloud servicescheat sheet will help. Consider it a guide for cloud directories — a quickreference sheet for what each vendor calls the same service.However, you can also use this as a starting point. You’ll need to do yourhomework to get a more nuanced understanding of what distinguishes theofferings from one another. Follow some of the links throughout this piece andtake that next step in dissecting these offerings.That’s because not all services are equal — each has its own set of featuresand capabilities, and the functionality might vary widely across platforms.And just because a provider doesn’t have a designated service in one of thesecategories, that doesn’t mean it’s impossible to achieve the same objective.For example, Google Cloud doesn’t offer an explicit disaster recovery service,but it’s certainly capable of supporting DR.Here is our cloud services cheat sheet of the services available on AWS,Google Cloud and Azure. The list is broken down by category to help you startyour cross-cloud analysis.

AI and machine learning

| AWS | Azure | Google Cloud —|—|—|— AI containers | AWS Deep Learning Containers | GPU support on AKS | DeepLearning Containers AI machine images | AWS Deep Learning AMIs | Data Science Virtual Machines |Deep Learning VM Image Chat bots builder | Amazon Lex | Azure Bot Service, QnA Maker | Dialogflow Data labeling | Amazon SageMaker Ground Truth | Azure Machine Learning datalabeling | Cloud Data Labeling Document extraction, image content analysis | Amazon Textract | Azure FormRecognizer, Ink Recognizer, Computer Vision, Custom Vision | Vision API Image and video recognition, indexing | Amazon Rekognition | Azure Face, VideoIndexer | Video AI Inference accelerator | Amazon Elastic Inference | GPUs on AKS | Cloud TPU,Edge TPU Language recognition, sentiment analysis | Amazon Comprehend | LanguageUnderstanding, Text Analytics | Natural Language Language translation | Amazon Translate | Speech Translation, Translator |Translation Machine learning hardware | AWS Inferentia, AWS Trainium (preview*) | FPGA |Cloud TPU Managed machine learning platform | Amazon SageMaker | Azure Machine Learning| Cloud AutoML Online fraud detection | Amazon Fraud Detector | N/A | reCAPTCHA Enterprise Prediction review and moderation | Amazon Augmented AI, Amazon SageMakerClarify | Azure Content Moderator | N/A Recommendation integration | Amazon Personalize | Personalizer |Recommendations AI (preview) Speech recognition | Amazon Transcribe | Speaker Recognition, Speech to Text |Cloud Speech-to-Text API Text-to-speech | Amazon Polly | Text to Speech | Cloud Text-to-Speech API Time-series forecasting | Amazon Forecast | N/A | N/A Vision/speech modeling packaged devices | AWS DeepLens | Azure Kinect DK | N/A


| AWS | Azure | Google Cloud —|—|—|— Big data processing | Amazon EMR | Azure Databricks, Azure HDInsight |Dataproc Business analytics | Amazon QuickSight | Power BI Embedded | Looker, GoogleData Studio Data lake creation | Amazon HealthLake (preview), AWS Lake Formation | AzureData Lake Storage | Cloud Storage Data sharing | AWS Data Exchange, AWS Lake Formation | Azure Data Share |Cloud Dataprep (partnership with Trifacta) Data warehousing | Amazon Redshift | Azure Synapse Analytics | BigQuery ETL | AWS Glue, Amazon Kinesis Data Firehose, Amazon SageMaker Data Wrangler |Azure Data Factory | Cloud Data Fusion, Dataflow, Dataproc Hosted Hadoop/Spark | Amazon EMR | Azure HDInsight | Dataproc Managed search | Amazon CloudSearch, Amazon Elasticsearch Service, AmazonKendra | Azure Cognitive Search, Bing Search services | Cloud Search Managed Kafka | Amazon Managed Streaming for Apache Kafka | Azure Event Hubsfor Apache Kafka | N/A (available through a partnership with Confluent) Real-time data streaming | Amazon Kinesis Data Analytics, Amazon Kinesis DataStreams | Azure Stream Analytics | Dataflow, Pub/Sub Query service, data exploration | Amazon Athena, Amazon Elasticsearch Service,Amazon Managed Service for Grafana (preview) | SQL Server ML Services, BigData Clusters (Spark), Data Lake Analytics, SQL Server Analysis Services,Azure Data Explorer | BigQuery


| AWS | Azure | Google Cloud —|—|—|— Blockchain | Amazon Managed Blockchain, Amazon Quantum Ledger Database (QLDB)| Azure Blockchain Service (preview), Azure Blockchain Tokens (preview), AzureBlockchain Workbench (preview) | N/A In-memory caching | Amazon ElastiCache (Memcached, Redis) | Azure Cache forRedis | Cloud Memorystore NoSQL: Column-family | Amazon Keyspaces (for Apache Cassandra) | Azure CosmosDB | Cloud Bigtable NoSQL: Document | Amazon DocumentDB (with MongoDB compatibility), AmazonDynamoDB | Azure Cosmos DB | Cloud Firestore, Firebase Realtime Database NoSQL: Graph | Amazon Neptune | Azure Cosmos DB Gremlin API | N/A NoSQL: Key-value | Amazon DynamoDB, Amazon Keyspaces | Azure Cosmos DB, Tablestorage | Cloud Bigtable, Firestore Relational database management system | Amazon Aurora, Amazon RDS (MySQL,PostgreSQL, Oracle, SQL Server, MariaDB), Amazon RDS on VMware | AzureDatabase (MySQL, MariaDB, PostgreSQL), Azure SQL (Database, Edge, ManagedInstance) | Cloud SQL (MySQL, PostgreSQL, SQL Server), Cloud Spanner Time-series database | Amazon Timestream | Azure Time Series Insights | CloudBigtable

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