ANALISIS STRATEGI KOMUNIKASI PEMASARAN PERIKLANAN WORKSPACE 53 DALAM MEMASARKAN COWORKING SPACE DI KOTA BANDUNG
Bibliographic record
Abstract
Abstrak Perkembangan startup di Indonesia pada saat ini sangat berkembang pesat dan sangat beranekaragam. Indonesia pada saat ini berada pada peringkat kelima sebagai negara penghasil startup terbanyak setelah Amerika Serikat dengan jumlah 49.966, India sebanyak 6,666, Inggris 4.995, Kanada 2.547 dan Indonesia berjumlah 2.124. Dengan pertumbuhan startup yang pesat seperti ini membuat bisnis coworking space pun menjadi tumbuh subur. Di kota Bandung jumlah coworking space pada tahun 2019 berjumlah 33 coworking space, dan salah satunya adalah Workspace 53. Workspace 53 selama beroperasi target revenue perbulan selalu tidak tercapai. Ternyata hal ini disebabkan oleh komunikasi pemasaran periklanan yang belum efektif karena terbukti melalui Instagram ads analytics. Sehingga pemilik Workspace 53 pun harus menemukan suatu strategi komunikasi pemasaran yang mampu menarik perhatian konsumen. Penelitian ini akan diteliti menggunakan Analisis Gap dengan mencari nilai Gap antara Customers Expectation, Potential Customers Expectation dengan Company Expectation agar dapat menghasilkan rekomendasi untuk strategi komunikasi pemasaran periklanan Workspace 53 agar lebih baik kedepannya. Penelitian ini menggunakan metode kuantitatif dengan menggunakan kuesioner yang disebarkan kepada para responden sebagai sumber data, serta tujuan penelitian ini adalah deskriptif dengan menjelaskan gap antara customers expectation, potential customers expectation dan company expectation. Untuk mendapatkan Gap tersebut data diolah menggunakan Microsoft Excel dan diimplementasikan melalui spider chart atau radar chart agar dapat dilihat Gap pada setiap dimensi komunikasi pemasaran Clow dan Baack Method. Sehingga nantinya dapat ditemukan Gap positif dan Gap negatif setiap dimensi. Dari delapan dimensi yang diteliti, dimensi yang memiliki gap negatif tertinggi adalah dimensi identifable selling point pada indikator ke-18 yang mana iklan Workspace 53 belum menjelaskan keunggulan jasa yang ditawarkan, sementara dimensi yang memiliki gap positif tertinggi adalah dimensi ad clutter, yaitu pada indikator ke-23 yang mana tools tolak ukur keberhasilan iklan Workspace 53 dirasa sudah baik. Kata kunci: Komunikasi Pemasaran, Periklanan, Coworking Space dan Analisis Gap Abstract The development of startups in Indonesia is currently growing rapidly and is very diverse. Indonesia is currently ranked fifth as the most startup producing country after the United States with 49,966, India 6,666, Britain 4,995, Canada 2,547 and Indonesia totaling 2,124. With the rapid growth of startups like this, the coworking space business is flourishing. In the city of Bandung the number of coworking spaces in 2019 amounted to 33 coworking spaces, and one of them was Workspace 53. Workspace 53 during operation the monthly revenue target is always not achieved. Apparently this is caused by advertising marketing communication that has not been effective because it is proven through Instagram ads analytics. So the Workspace 53 owner must find a marketing communication strategy that is able to attract the attention of customers. This research will be examined using Gap Analysis by finding the value of Gap between Customers Expectation, Potential Customers Expectation in order to produce recommendations for Workspace 53 advertising marketing communication strategies to be better going forward. This study uses a quantitative method using a questionnaire distributed to respondents as a source of data, and the purpose of this study is descriptive by explaining the gap between customer expectation, potential customers expectation, company expectation To get this gap the data is processed using Microsoft Excel and implemented through a spider chart or radar chart so that the gap can be seen in every dimension, so that later it can be found positive and negative gaps for each dimension. Of the eight dimensions examined, the dimension that has the highest negative gap is the identifable selling point dimension on indicator number 18 where Workspace 53 adverts have not explained the superiority of the services offered, while the dimension that has the highest positive gap is the beating ad clutter dimension, namely the indicator number 23 which is a good benchmark for measuring the success of Workspace 53 ads.. Keywords : Marketing Communication, Advertising, Coworking Space, and Gap Analysis
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".