Verizon Ventures’ Mark Smith shares his thoughts on how data science can be leveraged to better identify, target, deliver and measure the results of marketing programs. Below is the full article which originally appeared in NVCA’s The Corporate Venture Connection newsletter.
Verizon Ventures has invested in advertising and marketing technology startups since our formation. Our passion for the space remains strong even through many ups-and-downs of this endlessly transforming industry sector. In recent years it is increasingly characterized by greater levels of data capture and real time analytics on live data streams as well as advanced audience segmentation and individual behavioral modeling. Savvy entrepreneurs and technologists are continually pushing the boundaries of the social and data sciences to better identify, target, deliver and measure the results of marketing programs.
Many wonder what will happen with adtech/martech startups following consolidation that has taken place over the last few years and with increasingly dominant players like Facebook and Google in the mobile channel. We always keep an eye on public market valuations for independent adtech/martech companies — which are not great right now — and the level of new investments in private companies and IPOs in this sector which have slowed considerably. However, we remain convinced that in the long run smart adtech and martech entrepreneurs are very much worth seeking out and supporting and can provide good investment returns. For Verizon, the future is clear; in our data-driven world, big data, data analytics, data-driven decision-making, and artificial intelligence will provide substantial opportunities for bold entrepreneurs and brave investors in adtech/martech.
Making intelligent use of data to target the right audiences
One of the many interesting technologies we follow today centers on machine learning– and specifically how to use continuously available and updated huge new data sets that can now captured and are available (or previously ignored) in marketing planning and execution. The many varied and sometimes complementary layers of user, location, contextual, intent and other data can provide powerful predictions as to who, when and how brand messaging will impact consumers. Coupled with automated programmatic technologies the potential for Big Data and AI is powerful in this industry.
Data capture has to face the cat-and-mouse game with ad blocking. While overall it is a serious and concerning development, it is also driving a movement toward native ads. We see a rise in celebrity endorsements, resulting in ads that are so compelling people would do not want to block them. Likewise, with social media, we see more contextually relevant ads in stream because the major platforms have so much information on their users, they are able to deliver extremely targeted ads and need not rely on pop-ups or other mechanisms that turn off users.
Evolving startups to meet the challenges of today
AdTheorent is a company that has evolved along with the industry over the years. The team is comprised of data scientists tying together users with addresses on different devices. Initially they focused on sifting through mounds of data to find the best match to get advertisers the biggest bang for their buck. Their real time machine learning technology platform evolved for applicability beyond advertising. It’s companies like this — who can improve and expand their technologies to meet new challenges — that are the ones to watch.
More ad tech innovation to come in 2017 will be around tracking sales offline — tools that truly measure which messages lead to sales in retail stores, and then using that to help recommend the best way to use ad dollars. New content platforms such as virtual and augmented reality are going to be interesting to watch as adoption becomes more widespread, to see how ad tech innovators insert ads and track the data from this new source. The next few years are bound to be exciting.
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