Do we really need to remind anybody about the fact that email (and email marketing) isn’t going anywhere anytime soon? If we did, we’d just flash this study by Grup Radicati on them, containing such zingers as…

Pada akhir tahun 2019, jumlah pengguna email di seluruh dunia akan meningkat menjadi lebih dari 2,9 miliar. Lebih dari sepertiga populasi dunia akan menggunakan email pada akhir tahun 2019.

For those of us who work in email? Stats like that are pretty temptacious, as the kids say. But hari ini email isn’t your mom or dad’s email. The continuing success of email lies, in large part, to how its ability to evolve. Going mobile put email into a lot more pockets, for instance. 

Kini, dengan hadirnya teknologi terkait AI, email Anda campaigns dapat menjadi lebih tepat, menarik, dan efektif daripada sebelumnya.

The arrival of email AI? That’s so 2018 

At the end of 2018, PwC said it had surveyed U.S. execs, and found 27% of them claiming to be sudah implementing AI in multiple areas. 

On the global front, 30% perusahaan di seluruh dunia will be using AI in at least one of their sales processes by 2020. But only 17% of email marketers considering automation tools gave any thought to incorporating AI.

The laggards might not realize the impact AI has already had on the email ecosystem. One very visible example was how Gmail handles email classification using Natural Language Processing (NLP) to filter incoming emails as Primary, Social, or Promotions messages. 

Here’s a penjelasan yang cukup bagus of how NLP does its job, presented as a primer for coders who want to hack up a spam filter. But if you aren’t interested in all the plumbing, that’s cool. One thing worth remembering, though? NLP and machine learning are only branches of the bigger, broader category “AI” and have specific goals.  

• NLP is intended to read, decipher, understand, and make sense of human language in a manner that’s useful in machine-human interaction. 

• Pembelajaran mesin melibatkan penerapan algoritme dan model statistik sehingga komputer dapat membuat keputusan dan melakukan tugas tanpa instruksi eksplisit dengan mengenali pola dalam data dan menarik kesimpulan.

Saat ini, ada beberapa alat dan taktik di mana NLP dan pembelajaran mesin digunakan untuk meningkatkan program email. Mari kita lihat beberapa tempat di mana Anda dapat mengintegrasikannya ke dalam campaigns Anda, bolehkah kita...?

Pengujian

With machine learning, you can now execute pengujian bandit bersenjata banyak. If you’re used to split testing, brace yourself: Now you’ll be able to run tests terus menerus and put your findings to work segera. Over time, you’ll gradually optimize your results, and simultaneously be able to test content and messaging while also sending your best-performing variant out to prospects or customers.

How’s it done? You set up a campaign and a few email variations, and machine learning does the rest, running tests throughout your campaign and fine-tuning it on the basis of test data. What can you test? Pretty much anything you’re already testing, from copy to design to images to timing. 

Penulisan naskah

Pembelajaran mesin dan NLP - dan sepupunya, Natural Language Genration (NLG) - dimanfaatkan oleh beberapa penyedia layanan untuk memberikan solusi yang dapat menghasilkan baris subjek dan salinan lainnya.

Take a company like Persado, for instance: Its “message machine” applies its grasp of natural language to create copy that speaks in the marketer’s “brand voice,” leveraging a huge database of tagged and scored works in 25 languages, a database that evolves over time as machine learning delivers insights (and makes judgments) about which messages hold the most appeal for your target audience.

Batu ujian, as another example, compares your subject line against a database of 21 billion emails, as well as industry trends, to predict its likely impression, click and conversion rates.

Rasa.io automated the newsletter creation process, and uses machine learning to optimize content based on each recipient’s behaviors to provide 1:1 personalization that’s “disesuaikan dengan minat dan kepribadian unik pelanggan Anda, tanpa waktu yang dibutuhkan untuk mengkurasi email Anda secara manual."

Janji

Want to pull off a little real-time content optimization to drive engagement? Cordial says it can “ingest and process customer event, behavior, and purchase data from virtually any source,” so messages can be dispatched across multiple channels, based on sampai-ke-kanan-ini-seketika behavioral data. So onboarding, re-engagement campaigns, and other triggered emails can be aligned with what they’re interested in this very moment.

Another way to engage? Add a personal touch. Well, a virtual personal touch: Conversica proudly claims to deliver “personalized human touch at scale” through AI sales assistants that reach out to a user within minutes of him or her showing interest in your brand or inventory via email or SMS. 

If you’re worried the “conversation” reads like robo-copy, they claim the AI “empathizes” effectively by analyzing replies to tailor the right responses.  Moreover, the platform isn’t intended simply for initial engagement or onboarding but can handle routine dialogues throughout the entire customer journey.

Segmentasi

For companies investing in customer data management platforms, being able to milk the greatest possible insight and benefits from big data to deliver highly personalized user experiences, especially in email, is an obvious concern. 

A machine learning solution that’s connected to these potentially enormous pools of data can do insightful segmentation in ways no human being – or boiler room full of human beings – ever could, making continual adjustments and uncovering new associations, even generating product new segments where none were visible before.  SimMachines is one of these providers, calling their particular flavor “dynamic predictive segmentation.” 

Pengiriman prediktif

If you haven’t heard of it before, that’s because itu adalah kerutan baru in applying machine learning to email. By analyzing the behavior of trillions of emails, predictive analytics and machine learning are able to optimize delivery and the overall health of an email program.

This means real-time insights are available about deliverability and performance issues, problems can be identified before they happen, and data-driven recommendations can be made about how to optimize engagement and performance.  Outages can be avoided – while ROI is maximized.

And if you’ll allow just one self-plug? It’s new ke game because this platform, Sinyal SparkPost, is the first and only email intelligence platform of its kind in the industry, and we’re proud to be offering it.

Ini adalah ledakan AI-untuk-email

Ini hanyalah beberapa area di mana AI, NLP, dan pembelajaran mesin memberikan dampak masa kini di email marketing. Jika Anda berpikir bahwa ini adalah puncak gunung es - atau tetesan pertama yang melewati pintu air - Anda mungkin benar.

One way to see how feverish a new technology segment is getting is to see how many companies and startups have hung out a shingle, using investor or job sites like AngelList. Right now, a search for “email AI” there menunjukkan lebih dari 600 perusahaan in the space, and there’ll be more to come.

In other words, there’ll eventually be an AI add-on for every facet of your email program.  In the meantime? Putting today’s existing AI tools to work already offers banyak of potential for discovering how NLP and machine learning can improve the way you’re using a veteran marketing channel that’s just as leading-edge as ever.